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Recognizing human actions using histogram of local binary patterns
Proceedings of the 2013 IEEE/SICE International Symposium on System Integration, 2013Human action recognition from video clips has become an active research field in recent years. Each action has its unique shape and a motion sequence can be suitably represented by a histogram. In this paper a histogram based action recognition method is presented. Motion history images are a good spatiotemporal template for action representation.
Sk. Md. Masudul Ahsan +3 more
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Data-driven techniques for smoothing histograms of local binary patterns
Pattern Recognition, 2016Local binary pattern histograms have proved very successful texture descriptors. Despite this success, the description procedure bears some drawbacks that are still lacking solutions in the literature. One of the problems arises when the number of extractable local patterns reduces while their dimension increases rendering the output histogram ...
Ylioinas, J +3 more
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Face description and identification using histogram sequence of local binary pattern
2015 Seventh International Conference on Advanced Computational Intelligence (ICACI), 2015Local detail features of face are important bases for recognizing different persons. For its invariant to monotonic gray-scale transformations and it's a non-parametric kernel which summarizes the local special structure of an image, the Local Binary Pattern (LBP) has becoming a popular technique for face representation.
Wei Ge, Wei Quan, Chunling Han
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Histogram of spatio temporal local binary patterns for human action recognition
2014 Joint 7th International Conference on Soft Computing and Intelligent Systems (SCIS) and 15th International Symposium on Advanced Intelligent Systems (ISIS), 2014Recognizing human action from video sequences has lots of applications that make it an interesting research subject. Motion History Image (MHI) is a good spatio-temporal template to represent the distinctive profile of an action using a single image. However, in this paper, we use Local Binary Patterns (LBP) to extract the highlighted features from the
Sk. Md. Masudul Ahsan +3 more
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Eye states detection by boosting Local Binary Pattern Histogram features
2008 15th IEEE International Conference on Image Processing, 2008In this paper, we propose a novel method for eye states detection. The detection of eye states is treated as an appearance based binary classification problem. The whole eye region is first scanned by a series of blocks with various locations and scales. The Local Binary Pattern Histogram (LBPH) is then extracted from each block to form a descriptor of
Cui Xu, Ying Zheng, Zengfu Wang
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Multi-scale Local Binary Pattern histogram for gender classification
2015 8th International Congress on Image and Signal Processing (CISP), 2015LBP (Local Binary Pattern) is a commonly used operator to extract LBPH (LBP histogram) of an image for local texture description. For gender classification, we proposed an innovative method by extracting multi-scale LBPH in DoG (Difference of Gaussian) space in this paper.
Yanan Xu, Yong Zhao, Yongjun Zhang
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Face Recognition Based on Adaptive Soft Histogram Local Binary Patterns
2013In this paper we propose the adaptive soft histogram local binary pattern (ASLBP) for face recognition. ASLBP is an extension of the soft histogram local binary pattern (SLBP). Different from the local binary pattern (LBP) and its variants, ASLBP is based on adaptively learning the soft margin of decision boundaries with the aim to improve recognition ...
Huixing Ye +3 more
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Hardware design of histograms of oriented gradients based on local binary pattern and binarization
2016 IEEE Asia Pacific Conference on Circuits and Systems (APCCAS), 2016Histograms of oriented gradients (HOG) are widely used to extract image features for pedestrian detection, but the involved complex computations are not amenable for hardware implementation. This paper presents a simplification of HOG using local binary patterns for gradient and magnitude computation.
Shen-Fu Hsiao +2 more
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Sparse local binary pattern histograms for face recognition with limited training samples
Proceedings of the 2014 ACM Southeast Regional Conference, 2014One of the harder problems in facial recognition is the Single Sample per Person (SSPP) problem, where only one training image is available for a facial recognition model. Such a problem exists in practical applications such as the OSCARS which is a face recognition for classroom attendance checking.
David Caleb Robinson, Jianxia Xue
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New face recognition method based on local binary pattern histogram
2014 15th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering (STA), 2014Face recognition is one of the most important tasks in computer vision and biometrics where many algorithms have been developed. The Local Binary Pattern (LBP) has been proved to be effective for facial image representation and analysis, but it is too local to be robust.
C. Taouche +4 more
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