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Publisher: Hindawi   (Total: 288 journals)

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Showing 1 - 200 of 288 Journals sorted alphabetically
Abstract and Applied Analysis     Open Access   (Followers: 3, SJR: 0.512, h-index: 32)
Active and Passive Electronic Components     Open Access   (Followers: 7, SJR: 0.157, h-index: 15)
Advances in Acoustics and Vibration     Open Access   (Followers: 33, SJR: 0.259, h-index: 6)
Advances in Aerospace Engineering     Open Access   (Followers: 52)
Advances in Agriculture     Open Access   (Followers: 8)
Advances in Artificial Intelligence     Open Access   (Followers: 15)
Advances in Astronomy     Open Access   (Followers: 34, SJR: 0.351, h-index: 17)
Advances in Bioinformatics     Open Access   (Followers: 17, SJR: 0.421, h-index: 8)
Advances in Chemistry     Open Access   (Followers: 20)
Advances in Civil Engineering     Open Access   (Followers: 37, SJR: 0.338, h-index: 8)
Advances in Condensed Matter Physics     Open Access   (Followers: 10, SJR: 0.248, h-index: 10)
Advances in Decision Sciences     Open Access   (Followers: 3, SJR: 0.231, h-index: 6)
Advances in Electronics     Open Access   (Followers: 63)
Advances in Fuzzy Systems     Open Access   (Followers: 5, SJR: 0.258, h-index: 7)
Advances in Hematology     Open Access   (Followers: 10, SJR: 0.892, h-index: 18)
Advances in High Energy Physics     Open Access   (Followers: 18, SJR: 0.892, h-index: 19)
Advances in Human-Computer Interaction     Open Access   (Followers: 19, SJR: 0.439, h-index: 9)
Advances in Materials Science and Engineering     Open Access   (Followers: 30, SJR: 0.263, h-index: 11)
Advances in Mathematical Physics     Open Access   (Followers: 3, SJR: 0.332, h-index: 10)
Advances in Medicine     Open Access   (Followers: 2)
Advances in Meteorology     Open Access   (Followers: 19, SJR: 0.498, h-index: 10)
Advances in Multimedia     Open Access   (Followers: 1, SJR: 0.191, h-index: 10)
Advances in Nonlinear Optics     Open Access   (Followers: 6)
Advances in Numerical Analysis     Open Access   (Followers: 4)
Advances in Nursing     Open Access   (Followers: 27)
Advances in Operations Research     Open Access   (Followers: 12, SJR: 0.343, h-index: 7)
Advances in Optical Technologies     Open Access   (Followers: 3, SJR: 0.283, h-index: 16)
Advances in OptoElectronics     Open Access   (Followers: 5, SJR: 0.973, h-index: 16)
Advances in Orthopedics     Open Access   (Followers: 8)
Advances in Pharmacological Sciences     Open Access   (Followers: 7, SJR: 0.695, h-index: 13)
Advances in Physical Chemistry     Open Access   (Followers: 9, SJR: 0.297, h-index: 7)
Advances in Power Electronics     Open Access   (Followers: 29, SJR: 0.26, h-index: 6)
Advances in Preventive Medicine     Open Access   (Followers: 5)
Advances in Public Health     Open Access   (Followers: 23)
Advances in Software Engineering     Open Access   (Followers: 10)
Advances in Tribology     Open Access   (Followers: 12, SJR: 0.267, h-index: 6)
Advances in Urology     Open Access   (Followers: 9, SJR: 0.629, h-index: 16)
Advances in Virology     Open Access   (Followers: 7, SJR: 1.04, h-index: 12)
AIDS Research and Treatment     Open Access   (Followers: 3, SJR: 1.125, h-index: 14)
Analytical Cellular Pathology     Open Access   (Followers: 2, SJR: 0.334, h-index: 12)
Anatomy Research Intl.     Open Access   (Followers: 2)
Anemia     Open Access   (Followers: 5, SJR: 0.991, h-index: 11)
Anesthesiology Research and Practice     Open Access   (Followers: 13, SJR: 0.513, h-index: 12)
Applied and Environmental Soil Science     Open Access   (Followers: 16, SJR: 0.53, h-index: 9)
Applied Bionics and Biomechanics     Open Access   (Followers: 8, SJR: 0.23, h-index: 13)
Applied Computational Intelligence and Soft Computing     Open Access   (Followers: 11)
Archaea     Open Access   (Followers: 3, SJR: 1.248, h-index: 27)
Arthritis     Open Access   (Followers: 5)
Autism Research and Treatment     Open Access   (Followers: 25)
Autoimmune Diseases     Open Access   (Followers: 3, SJR: 0.909, h-index: 17)
Behavioural Neurology     Open Access   (Followers: 9, SJR: 0.696, h-index: 34)
Biochemistry Research Intl.     Open Access   (Followers: 6, SJR: 1.085, h-index: 17)
Bioinorganic Chemistry and Applications     Open Access   (Followers: 9, SJR: 0.286, h-index: 19)
BioMed Research Intl.     Open Access   (Followers: 4, SJR: 0.725, h-index: 59)
Biotechnology Research Intl.     Open Access   (Followers: 1)
Bone Marrow Research     Open Access   (Followers: 2)
Canadian J. of Gastroenterology & Hepatology     Open Access   (Followers: 5, SJR: 0.856, h-index: 53)
Canadian J. of Infectious Diseases and Medical Microbiology     Open Access   (Followers: 5, SJR: 0.409, h-index: 25)
Canadian Respiratory J.     Open Access   (Followers: 1, SJR: 0.503, h-index: 42)
Cardiology Research and Practice     Open Access   (Followers: 8, SJR: 0.941, h-index: 17)
Case Reports in Anesthesiology     Open Access   (Followers: 10)
Case Reports in Cardiology     Open Access   (Followers: 3)
Case Reports in Critical Care     Open Access   (Followers: 8)
Case Reports in Dentistry     Open Access   (Followers: 5)
Case Reports in Dermatological Medicine     Open Access   (Followers: 2)
Case Reports in Emergency Medicine     Open Access   (Followers: 14)
Case Reports in Endocrinology     Open Access   (Followers: 1, SJR: 0.326, h-index: 1)
Case Reports in Gastrointestinal Medicine     Open Access   (Followers: 2)
Case Reports in Genetics     Open Access   (Followers: 1)
Case Reports in Hematology     Open Access   (Followers: 5)
Case Reports in Hepatology     Open Access   (Followers: 1)
Case Reports in Immunology     Open Access   (Followers: 4)
Case Reports in Infectious Diseases     Open Access   (Followers: 5)
Case Reports in Medicine     Open Access   (Followers: 2)
Case Reports in Nephrology     Open Access   (Followers: 4)
Case Reports in Neurological Medicine     Open Access   (Followers: 1)
Case Reports in Obstetrics and Gynecology     Open Access   (Followers: 10)
Case Reports in Oncological Medicine     Open Access   (Followers: 2)
Case Reports in Ophthalmological Medicine     Open Access   (Followers: 3)
Case Reports in Orthopedics     Open Access   (Followers: 5)
Case Reports in Otolaryngology     Open Access   (Followers: 6)
Case Reports in Pathology     Open Access   (Followers: 5)
Case Reports in Pediatrics     Open Access   (Followers: 6)
Case Reports in Psychiatry     Open Access   (Followers: 12)
Case Reports in Pulmonology     Open Access   (Followers: 3)
Case Reports in Radiology     Open Access   (Followers: 8)
Case Reports in Rheumatology     Open Access   (Followers: 5)
Case Reports in Surgery     Open Access   (Followers: 11)
Case Reports in Transplantation     Open Access  
Case Reports in Urology     Open Access   (Followers: 8)
Case Reports in Vascular Medicine     Open Access  
Case Reports in Veterinary Medicine     Open Access   (Followers: 6)
Child Development Research     Open Access   (Followers: 16)
Chinese J. of Engineering     Open Access   (Followers: 2)
Chinese J. of Mathematics     Open Access  
Cholesterol     Open Access   (Followers: 1, SJR: 0.906, h-index: 12)
Chromatography Research Intl.     Open Access   (Followers: 6)
Complexity     Hybrid Journal   (Followers: 6, SJR: 0.526, h-index: 27)
Computational and Mathematical Methods in Medicine     Open Access   (Followers: 2, SJR: 0.415, h-index: 22)
Computational Intelligence and Neuroscience     Open Access   (Followers: 10, SJR: 0.232, h-index: 30)
Contrast Media & Molecular Imaging     Open Access   (Followers: 3, SJR: 0.932, h-index: 34)
Critical Care Research and Practice     Open Access   (Followers: 10, SJR: 0.916, h-index: 14)
Current Gerontology and Geriatrics Research     Open Access   (Followers: 9, SJR: 0.8, h-index: 12)
Depression Research and Treatment     Open Access   (Followers: 13, SJR: 0.77, h-index: 11)
Dermatology Research and Practice     Open Access   (Followers: 3, SJR: 0.576, h-index: 15)
Diagnostic and Therapeutic Endoscopy     Open Access   (SJR: 0.651, h-index: 18)
Discrete Dynamics in Nature and Society     Open Access   (Followers: 5, SJR: 0.323, h-index: 24)
Disease Markers     Open Access   (Followers: 1, SJR: 0.774, h-index: 49)
Education Research Intl.     Open Access   (Followers: 19)
Emergency Medicine Intl.     Open Access   (Followers: 7)
Enzyme Research     Open Access   (Followers: 3, SJR: 0.457, h-index: 18)
Evidence-based Complementary and Alternative Medicine     Open Access   (Followers: 20, SJR: 0.615, h-index: 50)
Experimental Diabetes Research     Open Access   (Followers: 14, SJR: 1.591, h-index: 30)
Gastroenterology Research and Practice     Open Access   (Followers: 2, SJR: 0.664, h-index: 21)
Genetics Research Intl.     Open Access   (Followers: 1)
Geofluids     Open Access   (Followers: 4, SJR: 0.693, h-index: 38)
HPB Surgery     Open Access   (Followers: 4, SJR: 0.798, h-index: 22)
Infectious Diseases in Obstetrics and Gynecology     Open Access   (Followers: 5, SJR: 0.976, h-index: 34)
Interdisciplinary Perspectives on Infectious Diseases     Open Access   (Followers: 1, SJR: 0.763, h-index: 15)
Intl. J. of Aerospace Engineering     Open Access   (Followers: 71, SJR: 0.241, h-index: 6)
Intl. J. of Agronomy     Open Access   (Followers: 5, SJR: 0.223, h-index: 2)
Intl. J. of Alzheimer's Disease     Open Access   (Followers: 11, SJR: 1.193, h-index: 25)
Intl. J. of Analysis     Open Access  
Intl. J. of Analytical Chemistry     Open Access   (Followers: 20, SJR: 0.157, h-index: 2)
Intl. J. of Antennas and Propagation     Open Access   (Followers: 11, SJR: 0.385, h-index: 15)
Intl. J. of Atmospheric Sciences     Open Access   (Followers: 21)
Intl. J. of Biodiversity     Open Access   (Followers: 4)
Intl. J. of Biomaterials     Open Access   (Followers: 4, SJR: 0.485, h-index: 10)
Intl. J. of Biomedical Imaging     Open Access   (Followers: 3, SJR: 0.581, h-index: 23)
Intl. J. of Breast Cancer     Open Access   (Followers: 13)
Intl. J. of Cell Biology     Open Access   (Followers: 3, SJR: 2.658, h-index: 25)
Intl. J. of Chemical Engineering     Open Access   (Followers: 7, SJR: 0.361, h-index: 10)
Intl. J. of Chronic Diseases     Open Access   (Followers: 1)
Intl. J. of Computer Games Technology     Open Access   (Followers: 9, SJR: 0.213, h-index: 12)
Intl. J. of Corrosion     Open Access   (Followers: 10, SJR: 0.19, h-index: 7)
Intl. J. of Dentistry     Open Access   (Followers: 6, SJR: 0.558, h-index: 11)
Intl. J. of Differential Equations     Open Access   (Followers: 7, SJR: 0.363, h-index: 11)
Intl. J. of Digital Multimedia Broadcasting     Open Access   (Followers: 5, SJR: 0.144, h-index: 10)
Intl. J. of Electrochemistry     Open Access   (Followers: 8)
Intl. J. of Endocrinology     Open Access   (Followers: 4, SJR: 0.961, h-index: 24)
Intl. J. of Engineering Mathematics     Open Access   (Followers: 5)
Intl. J. of Food Science     Open Access   (Followers: 3)
Intl. J. of Forestry Research     Open Access   (Followers: 3)
Intl. J. of Genomics     Open Access   (Followers: 2, SJR: 0.721, h-index: 7)
Intl. J. of Hepatology     Open Access   (Followers: 4)
Intl. J. of Hypertension     Open Access   (Followers: 6, SJR: 0.823, h-index: 20)
Intl. J. of Inflammation     Open Access   (SJR: 0.876, h-index: 14)
Intl. J. of Inorganic Chemistry     Open Access   (Followers: 3)
Intl. J. of Mathematics and Mathematical Sciences     Open Access   (Followers: 3, SJR: 0.346, h-index: 27)
Intl. J. of Medicinal Chemistry     Open Access   (Followers: 5)
Intl. J. of Microbiology     Open Access   (Followers: 4, SJR: 1.006, h-index: 18)
Intl. J. of Navigation and Observation     Open Access   (Followers: 20, SJR: 0.411, h-index: 7)
Intl. J. of Nephrology     Open Access   (Followers: 1, SJR: 0.926, h-index: 14)
Intl. J. of Oceanography     Open Access   (Followers: 7)
Intl. J. of Optics     Open Access   (Followers: 7, SJR: 0.262, h-index: 7)
Intl. J. of Otolaryngology     Open Access   (Followers: 3)
Intl. J. of Partial Differential Equations     Open Access   (Followers: 2)
Intl. J. of Pediatrics     Open Access   (Followers: 6)
Intl. J. of Peptides     Open Access   (Followers: 4, SJR: 0.73, h-index: 16)
Intl. J. of Photoenergy     Open Access   (Followers: 2, SJR: 0.348, h-index: 28)
Intl. J. of Plant Genomics     Open Access   (Followers: 4, SJR: 1.578, h-index: 20)
Intl. J. of Polymer Science     Open Access   (Followers: 24, SJR: 0.265, h-index: 11)
Intl. J. of Population Research     Open Access   (Followers: 2)
Intl. J. of Quality, Statistics, and Reliability     Open Access   (Followers: 15, SJR: 0.345, h-index: 4)
Intl. J. of Reconfigurable Computing     Open Access   (SJR: 0.182, h-index: 8)
Intl. J. of Reproductive Medicine     Open Access   (Followers: 4)
Intl. J. of Rheumatology     Open Access   (Followers: 4, SJR: 1.015, h-index: 18)
Intl. J. of Rotating Machinery     Open Access   (Followers: 2, SJR: 0.402, h-index: 19)
Intl. J. of Spectroscopy     Open Access   (Followers: 6)
Intl. J. of Stochastic Analysis     Open Access   (Followers: 3, SJR: 0.234, h-index: 19)
Intl. J. of Surgical Oncology     Open Access   (Followers: 1, SJR: 0.753, h-index: 11)
Intl. J. of Telemedicine and Applications     Open Access   (Followers: 4, SJR: 0.757, h-index: 14)
Intl. J. of Vascular Medicine     Open Access   (SJR: 0.865, h-index: 16)
Intl. J. of Zoology     Open Access   (Followers: 1, SJR: 0.389, h-index: 8)
Intl. Scholarly Research Notices     Open Access   (Followers: 193)
ISRN Astronomy and Astrophysics     Open Access   (Followers: 6)
J. of Addiction     Open Access   (Followers: 12)
J. of Advanced Transportation     Hybrid Journal   (Followers: 12, SJR: 0.911, h-index: 24)
J. of Aerodynamics     Open Access   (Followers: 5)
J. of Aging Research     Open Access   (Followers: 6, SJR: 1.259, h-index: 23)
J. of Analytical Methods in Chemistry     Open Access   (Followers: 1, SJR: 0.296, h-index: 13)
J. of Applied Chemistry     Open Access   (Followers: 4)
J. of Applied Mathematics     Open Access   (Followers: 2, SJR: 0.341, h-index: 22)
J. of Biomedical Education     Open Access   (Followers: 3)
J. of Blood Transfusion     Open Access   (Followers: 1)
J. of Botany     Open Access   (Followers: 3, SJR: 0.101, h-index: 2)
J. of Cancer Epidemiology     Open Access   (Followers: 5, SJR: 1.427, h-index: 12)
J. of Chemistry     Open Access   (Followers: 5, SJR: 0.225, h-index: 11)
J. of Combustion     Open Access   (Followers: 22, SJR: 0.27, h-index: 8)
J. of Complex Analysis     Open Access   (Followers: 3)
J. of Composites     Open Access   (Followers: 80)
J. of Computer Networks and Communications     Open Access   (Followers: 4, SJR: 0.257, h-index: 8)
J. of Construction Engineering     Open Access   (Followers: 8)
J. of Control Science and Engineering     Open Access   (Followers: 1, SJR: 0.299, h-index: 9)
J. of Diabetes Research     Open Access   (Followers: 12, SJR: 1.024, h-index: 13)
J. of Drug Delivery     Open Access   (Followers: 6, SJR: 4.523, h-index: 2)
J. of Electrical and Computer Engineering     Open Access   (Followers: 9, SJR: 0.225, h-index: 10)
J. of Energy     Open Access   (Followers: 2)
J. of Engineering     Open Access  
J. of Environmental and Public Health     Open Access   (Followers: 15, SJR: 1.136, h-index: 16)

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Journal Cover Advances in Multimedia
  [SJR: 0.191]   [H-I: 10]   [1 followers]  Follow
  This is an Open Access Journal Open Access journal
   ISSN (Print) 1687-5680 - ISSN (Online) 1687-5699
   Published by Hindawi Homepage  [288 journals]
  • Learning a Mid-Level Representation for Multiview Action Recognition

    • Abstract: Recognizing human actions in videos is an active topic with broad commercial potentials. Most of the existing action recognition methods are supposed to have the same camera view during both training and testing. And thus performances of these single-view approaches may be severely influenced by the camera movement and variation of viewpoints. In this paper, we address the above problem by utilizing videos simultaneously recorded from multiple views. To this end, we propose a learning framework based on multitask random forest to exploit a discriminative mid-level representation for videos from multiple cameras. In the first step, subvolumes of continuous human-centered figures are extracted from original videos. In the next step, spatiotemporal cuboids sampled from these subvolumes are characterized by multiple low-level descriptors. Then a set of multitask random forests are built upon multiview cuboids sampled at adjacent positions and construct an integrated mid-level representation for multiview subvolumes of one action. Finally, a random forest classifier is employed to predict the action category in terms of the learned representation. Experiments conducted on the multiview IXMAS action dataset illustrate that the proposed method can effectively recognize human actions depicted in multiview videos.
      PubDate: Tue, 20 Mar 2018 07:45:43 +000
  • Multifeature Fusion Detection Method for Fake Face Attack in Identity

    • Abstract: With the rise in biometric-based identity authentication, facial recognition software has already stimulated interesting research. However, facial recognition has also been subjected to criticism due to security concerns. The main attack methods include photo, video, and three-dimensional model attacks. In this paper, we propose a multifeature fusion scheme that combines dynamic and static joint analysis to detect fake face attacks. Since the texture differences between the real and the fake faces can be easily detected, LBP (local binary patter) texture operators and optical flow algorithms are often merged. Basic LBP methods are also modified by considering the nearest neighbour binary computing method instead of the fixed centre pixel method; the traditional optical flow algorithm is also modified by applying the multifusion feature superposition method, which reduces the noise of the image. In the pyramid model, image processing is performed in each layer by using block calculations that form multiple block images. The features of the image are obtained via two fused algorithms (MOLF), which are then trained and tested separately by an SVM classifier. Experimental results show that this method can improve detection accuracy while also reducing computational complexity. In this paper, we use the CASIA, PRINT-ATTACK, and REPLAY-ATTACK database to compare the various LBP algorithms that incorporate optical flow and fusion algorithms.
      PubDate: Thu, 08 Mar 2018 09:24:12 +000
  • Indian Classical Dance Action Identification and Classification with
           Convolutional Neural Networks

    • Abstract: Extracting and recognizing complex human movements from unconstrained online/offline video sequence is a challenging task in computer vision. This paper proposes the classification of Indian classical dance actions using a powerful artificial intelligence tool: convolutional neural networks (CNN). In this work, human action recognition on Indian classical dance videos is performed on recordings from both offline (controlled recording) and online (live performances, YouTube) data. The offline data is created with ten different subjects performing 200 familiar dance mudras/poses from different Indian classical dance forms under various background environments. The online dance data is collected from YouTube for ten different subjects. Each dance pose is occupied for 60 frames or images in a video in both the cases. CNN training is performed with 8 different sample sizes, each consisting of multiple sets of subjects. The remaining 2 samples are used for testing the trained CNN. Different CNN architectures were designed and tested with our data to obtain a better accuracy in recognition. We achieved a 93.33% recognition rate compared to other classifier models reported on the same dataset.
      PubDate: Mon, 22 Jan 2018 00:00:00 +000
  • Global Distribution Adjustment and Nonlinear Feature Transformation for
           Automatic Colorization

    • Abstract: Automatic colorization is generally classified into two groups: propagation-based methods and reference-based methods. In reference-based automatic colorization methods, color image(s) are used as reference(s) to reconstruct original color of a gray target image. The most important task here is to find the best matching pairs for all pixels between reference and target images in order to transfer color information from reference to target pixels. A lot of attractive local feature-based image matching methods have already been developed for the last two decades. Unfortunately, as far as we know, there are no optimal matching methods for automatic colorization because the requirements for pixel matching in automatic colorization are wholly different from those for traditional image matching. To design an efficient matching algorithm for automatic colorization, clustering pixel with low computational cost and generating descriptive feature vector are the most important challenges to be solved. In this paper, we present a novel method to address these two problems. In particular, our work concentrates on solving the second problem (designing a descriptive feature vector); namely, we will discuss how to learn a descriptive texture feature using scaled sparse texture feature combining with a nonlinear transformation to construct an optimal feature descriptor. Our experimental results show our proposed method outperforms the state-of-the-art methods in terms of robustness for color reconstruction for automatic colorization applications.
      PubDate: Wed, 10 Jan 2018 07:50:41 +000
  • Academic Activities Transaction Extraction Based on Deep Belief Network

    • Abstract: Extracting information about academic activity transactions from unstructured documents is a key problem in the analysis of academic behaviors of researchers. The academic activities transaction includes five elements: person, activities, objects, attributes, and time phrases. The traditional method of information extraction is to extract shallow text features and then to recognize advanced features from text with supervision. Since the information processing of different levels is completed in steps, the error generated from various steps will be accumulated and affect the accuracy of final results. However, because Deep Belief Network (DBN) model has the ability to automatically unsupervise learning of the advanced features from shallow text features, the model is employed to extract the academic activities transaction. In addition, we use character-based feature to describe the raw features of named entities of academic activity, so as to improve the accuracy of named entity recognition. In this paper, the accuracy of the academic activities extraction is compared by using character-based feature vector and word-based feature vector to express the text features, respectively, and with the traditional text information extraction based on Conditional Random Fields. The results show that DBN model is more effective for the extraction of academic activities transaction information.
      PubDate: Tue, 12 Dec 2017 09:15:01 +000
  • A Novel DBSCAN Based on Binary Local Sensitive Hashing and Binary-KNN

    • Abstract: We revisit the classic DBSCAN algorithm by proposing a series of strategies to improve its robustness to various densities and its efficiency. Unlike the original DBSCAN, we first use the binary local sensitive hashing (LSH) which enables faster region query for the neighbors of a data point. The binary data representation method based on neighborhood is then proposed to map the dataset into the Hamming space for faster cluster expansion. We define a core point based on binary influence space to enhance the robustness to various densities. Also, we propose a seed point selection method, which is based on influence space and neighborhood similarity, to select some seed points instead of all the neighborhood during cluster expansion. Consequently, the number of region queries can be decreased. The experimental results show that the improved algorithm can greatly improve the clustering speed under the premise of ensuring better algorithm clustering accuracy, especially for large-scale datasets.
      PubDate: Thu, 07 Dec 2017 09:04:48 +000
  • Vehicle Plate Detection in Car Black Box Video

    • Abstract: Internet services that share vehicle black box videos need a way to obfuscate license plates in uploaded videos because of privacy issues. Thus, plate detection is one of the critical functions that such services rely on. Even though various types of detection methods are available, they are not suitable for black box videos because no assumption about size, number of plates, and lighting conditions can be made. We propose a method to detect Korean vehicle plates from black box videos. It works in two stages: the first stage aims to locate a set of candidate plate regions and the second stage identifies only actual plates from candidates by using a support vector machine classifier. The first stage consists of five sequential substeps. At first, it produces candidate regions by combining single character areas and then eliminates candidate regions that fail to meet plate conditions through the remaining substeps. For the second stage, we propose a feature vector that captures the characteristics of plates in texture and color. For performance evaluation, we compiled our dataset which contains 2,627 positive and negative images. The evaluation results show that the proposed method improves accuracy and sensitivity by at least 5% and is 30 times faster compared with an existing method.
      PubDate: Tue, 28 Nov 2017 00:00:00 +000
  • Efficient Gabor Phase Based Illumination Invariant for Face Recognition

    • Abstract: This paper presents a novel Gabor phase based illumination invariant extraction method aiming at eliminating the effect of varying illumination on face recognition. Firstly, It normalizes varying illumination on face images, which can reduce the effect of varying illumination to some extent. Secondly, a set of 2D real Gabor wavelet with different directions is used for image transformation, and multiple Gabor coefficients are combined into one whole in considering spectrum and phase. Lastly, the illumination invariant is obtained by extracting the phase feature from the combined coefficients. Experimental results on the Yale B and the CMU PIE face database show that our method obtained a significant improvement over other related methods for face recognition under large illumination variation condition.
      PubDate: Mon, 27 Nov 2017 00:00:00 +000
  • General Framework of Reversible Watermarking Based on Asymmetric Histogram
           Shifting of Prediction Error

    • Abstract: This paper presents a general framework for the reversible watermarking based on asymmetric histogram shifting of prediction error, which is inspired by reversible watermarking of prediction error. Different from the conventional algorithms using single-prediction scheme to create symmetric histogram, the proposed method employs a multi-prediction scheme, which calculates multiple prediction values for the pixels. Then, the suitable value would be selected by two dual asymmetric selection functions to construct two asymmetric error histograms. Finally, the watermark is embedded in the two error histograms separately utilizing a complementary embedding strategy. The proposed framework provides a new perspective for the research of reversible watermarking, which brings about many benefits for the information security.
      PubDate: Thu, 23 Nov 2017 00:00:00 +000
  • A No-Reference Modular Video Quality Prediction Model for H.265/HEVC and
           VP9 Codecs on a Mobile Device

    • Abstract: We propose a modular no-reference video quality prediction model for videos that are encoded with H.265/HEVC and VP9 codecs and viewed on mobile devices. The impairments which can affect video transmission are classified into two broad types depending upon which layer of the TCP/IP model they originated from. Impairments from the network layer are called the network QoS factors, while those from the application layer are called the application/payload QoS factors. Initially we treat the network and application QoS factors separately and find out the 1 : 1 relationship between the respective QoS factors and the corresponding perceived video quality or QoE. The mapping from the QoS to the QoE domain is based upon a decision variable that gives an optimal performance. Next, across each group we choose multiple QoS factors and find out the QoE for such multifactor impaired videos by using an additive, multiplicative, and regressive approach. We refer to these as the integrated network and application QoE, respectively. At the end, we use a multiple regression approach to combine the network and application QoE for building the final model. We also use an Artificial Neural Network approach for building the model and compare its performance with the regressive approach.
      PubDate: Thu, 23 Nov 2017 00:00:00 +000
  • Deep Binary Representation for Efficient Image Retrieval

    • Abstract: With the fast growing number of images uploaded every day, efficient content-based image retrieval becomes important. Hashing method, which means representing images in binary codes and using Hamming distance to judge similarity, is widely accepted for its advantage in storage and searching speed. A good binary representation method for images is the determining factor of image retrieval. In this paper, we propose a new deep hashing method for efficient image retrieval. We propose an algorithm to calculate the target hash code which indicates the relationship between images of different contents. Then the target hash code is fed to the deep network for training. Two variants of deep network, DBR and DBR-v3, are proposed for different size and scale of image database. After training, our deep network can produce hash codes with large Hamming distance for images of different contents. Experiments on standard image retrieval benchmarks show that our method outperforms other state-of-the-art methods including unsupervised, supervised, and deep hashing methods.
      PubDate: Sun, 12 Nov 2017 07:15:25 +000
  • Hand Motion and Posture Recognition in a Network of Calibrated Cameras

    • Abstract: This paper presents a vision-based approach for hand gesture recognition which combines both trajectory and hand posture recognition. The hand area is segmented by fixed-range CbCr from cluttered and moving backgrounds and tracked by Kalman Filter. With the tracking results of two calibrated cameras, the 3D hand motion trajectory can be reconstructed. It is then modeled by dynamic movement primitives and a support vector machine is trained for trajectory recognition. Scale-invariant feature transform is employed to extract features on segmented hand postures, and a novel strategy for hand posture recognition is proposed. A gesture vector is introduced to recognize hand gesture as an entirety which combines the recognition results of motion trajectory and hand postures where a support vector machine is trained for gesture recognition based on gesture vectors.
      PubDate: Tue, 31 Oct 2017 11:48:00 +000
  • A Spectrum Sensing Method Based on Signal Feature and Clustering Algorithm
           in Cognitive Wireless Multimedia Sensor Networks

    • Abstract: In order to solve the problem of difficulty in determining the threshold in spectrum sensing technologies based on the random matrix theory, a spectrum sensing method based on clustering algorithm and signal feature is proposed for Cognitive Wireless Multimedia Sensor Networks. Firstly, the wireless communication signal features are obtained according to the sampling signal covariance matrix. Then, the clustering algorithm is used to classify and test the signal features. Different signal features and clustering algorithms are compared in this paper. The experimental results show that the proposed method has better sensing performance.
      PubDate: Thu, 26 Oct 2017 00:00:00 +000
  • Deep Learning for Person Reidentification Using Support Vector Machines

    • Abstract: Due to the variations of viewpoint, pose, and illumination, a given individual may appear considerably different across different camera views. Tracking individuals across camera networks with no overlapping fields is still a challenging problem. Previous works mainly focus on feature representation and metric learning individually which tend to have a suboptimal solution. To address this issue, in this work, we propose a novel framework to do the feature representation learning and metric learning jointly. Different from previous works, we represent the pairs of pedestrian images as new resized input and use linear Support Vector Machine to replace softmax activation function for similarity learning. Particularly, dropout and data augmentation techniques are also employed in this model to prevent the network from overfitting. Extensive experiments on two publically available datasets VIPeR and CUHK01 demonstrate the effectiveness of our proposed approach.
      PubDate: Tue, 10 Oct 2017 00:00:00 +000
  • SDP-Based Quality Adaptation and Performance Prediction in Adaptive
           Streaming of VBR Videos

    • Abstract: Recently, various adaptation methods have been proposed to cope with throughput fluctuations in HTTP adaptive streaming (HAS). However, these methods have mostly focused on constant bitrate (CBR) videos. Moreover, most of them are qualitative in the sense that performance metrics could only be obtained after a streaming session. In this paper, we propose a new adaptation method for streaming variable bitrate (VBR) videos using stochastic dynamic programming (SDP). With this approach, the system should have a probabilistic characterization along with the definition of a cost function that is minimized by a control strategy. Our solution is based on a new statistical model where the future streaming performance is directly related to the past bandwidth statistics. We develop mathematical models to predict and develop simulation models to measure the average performance of the adaptation policy. The experimental results show that the prediction models can provide accurate performance prediction which is useful in planning adaptation policy and that our proposed adaptation method outperforms the existing ones in terms of average quality and average quality switch.
      PubDate: Sun, 02 Jul 2017 09:10:39 +000
  • Moving Object Detection for Dynamic Background Scenes Based on
           Spatiotemporal Model

    • Abstract: Moving object detection in video streams is the first step of many computer vision applications. Background modeling and subtraction for moving detection is the most common technique for detecting, while how to detect moving objects correctly is still a challenge. Some methods initialize the background model at each pixel in the first N frames. However, it cannot perform well in dynamic background scenes since the background model only contains temporal features. Herein, a novel pixelwise and nonparametric moving object detection method is proposed, which contains both spatial and temporal features. The proposed method can accurately detect the dynamic background. Additionally, several new mechanisms are also proposed to maintain and update the background model. The experimental results based on image sequences in public datasets show that the proposed method provides the robustness and effectiveness in dynamic background scenes compared with the existing methods.
      PubDate: Sun, 18 Jun 2017 07:21:25 +000
  • Robust and Reversible Audio Watermarking by Modifying Statistical Features
           in Time Domain

    • Abstract: Robust and reversible watermarking is a potential technique in many sensitive applications, such as lossless audio or medical image systems. This paper presents a novel robust reversible audio watermarking method by modifying the statistic features in time domain in the way that the histogram of these statistical values is shifted for data hiding. Firstly, the original audio is divided into nonoverlapped equal-sized frames. In each frame, the use of three samples as a group generates a prediction error and a statistical feature value is calculated as the sum of all the prediction errors in the frame. The watermark bits are embedded into the frames by shifting the histogram of the statistical features. The watermark is reversible and robust to common signal processing operations. Experimental results have shown that the proposed method not only is reversible but also achieves satisfactory robustness to MP3 compression of 64 kbps and additive Gaussian noise of 35 dB.
      PubDate: Thu, 27 Apr 2017 00:00:00 +000
  • Strategies for Growing User Popularity through Retweet: An Empirical Study

    • Abstract: Web-based Social Networks (W-bSNs) have recently experienced a significant rise regarding users and the number of relations among them. Twitter is a case of W-bSN in which the relevance of the commentaries posted influences how users create new relations. The reputation of a user has a direct effect on the perception and opinions of other people and can be appropriately used to obtain advantages. The thought expressed by an influential user can produce, as an effect, which other users changed an idea about a topic. In this work, we present the design and results of the empirical study to analyze the cross influence among users, for their interest, and the messages they post and how relevant these messages are in how we create new relations. One of the main contributions of this approach is to analyze the behavior of users and the impact of the diversification of topics and the inclusion of additional resources to the tweet such as videos, images, or URLs. Finally, the experimental results show that the proposed strategies are efficient for all accounts.
      PubDate: Mon, 10 Apr 2017 00:00:00 +000
  • Commutative Watermarking-Encryption of Audio Data with Minimum Knowledge

    • Abstract: We present a scheme for commutative watermarking-encryption (CWE) of audio data and demonstrate its robustness against an important class of attacks, Time-Scale Modifications (TSM). In addition, we show how the proposed CWE scheme can be integrated into a cryptographic protocol enabling public verification of the embedded mark without disclosing the mark or the watermarking key used for embedding.
      PubDate: Mon, 20 Mar 2017 07:06:20 +000
  • Low Cost Skin Segmentation Scheme in Videos Using Two Alternative Methods
           for Dynamic Hand Gesture Detection Method

    • Abstract: Recent years have witnessed renewed interest in developing skin segmentation approaches. Skin feature segmentation has been widely employed in different aspects of computer vision applications including face detection and hand gestures recognition systems. This is mostly due to the attractive characteristics of skin colour and its effectiveness to object segmentation. On the contrary, there are certain challenges in using human skin colour as a feature to segment dynamic hand gesture, due to various illumination conditions, complicated environment, and computation time or real-time method. These challenges have led to the insufficiency of many of the skin color segmentation approaches. Therefore, to produce simple, effective, and cost efficient skin segmentation, this paper has proposed a skin segmentation scheme. This scheme includes two procedures for calculating generic threshold ranges in Cb-Cr colour space. The first procedure uses threshold values trained online from nose pixels of the face region. Meanwhile, the second procedure known as the offline training procedure uses thresholds trained out of skin samples and weighted equation. The experimental results showed that the proposed scheme achieved good performance in terms of efficiency and computation time.
      PubDate: Thu, 02 Mar 2017 08:15:02 +000
  • Salient Object Detection Based on Background Feature Clustering

    • Abstract: Automatic estimation of salient object without any prior knowledge tends to greatly enhance many computer vision tasks. This paper proposes a novel bottom-up based framework for salient object detection by first modeling background and then separating salient objects from background. We model the background distribution based on feature clustering algorithm, which allows for fully exploiting statistical and structural information of the background. Then a coarse saliency map is generated according to the background distribution. To be more discriminative, the coarse saliency map is enhanced by a two-step refinement which is composed of edge-preserving element-level filtering and upsampling based on geodesic distance. We provide an extensive evaluation and show that our proposed method performs favorably against other outstanding methods on two most commonly used datasets. Most importantly, the proposed approach is demonstrated to be more effective in highlighting the salient object uniformly and robust to background noise.
      PubDate: Thu, 09 Feb 2017 00:00:00 +000
  • Revealing Traces of Image Resampling and Resampling Antiforensics

    • Abstract: Image resampling is a common manipulation in image processing. The forensics of resampling plays an important role in image tampering detection, steganography, and steganalysis. In this paper, we proposed an effective and secure detector, which can simultaneously detect resampling and its forged resampling which is attacked by antiforensic schemes. We find that the interpolation operation used in the resampling and forged resampling makes these two kinds of image show different statistical behaviors from the unaltered images, especially in the high frequency domain. To reveal the traces left by the interpolation, we first apply multidirectional high-pass filters on an image and the residual to create multidirectional differences. Then, the difference is fit into an autoregressive (AR) model. Finally, the AR coefficients and normalized histograms of the difference are extracted as the feature. We assemble the feature extracted from each difference image to construct the comprehensive feature and feed it into support vector machines (SVM) to detect resampling and forged resampling. Experiments on a large image database show that the proposed detector is effective and secure. Compared with the state-of-the-art works, the proposed detector achieved significant improvements in the detection of downsampling or resampling under JPEG compression.
      PubDate: Thu, 12 Jan 2017 12:49:33 +000
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