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This paper proposes two sets of novel edge-texture features, Discriminative Robust Local Binary Pattern (DRLBP) and Ternary Pattern (DRLTP), for object recognition. By investigating the limitations of Local Binary Pattern (LBP), Local Ternary Pattern (LTP) and Robust LBP (RLBP), DRLBP and DRLTP are proposed as new features. They solve the problem of(More)
This paper proposes a quadratic classification approach on the subspace of Extended Histogram of Gradients (ExHoG) for human detection. By investigating the limitations of Histogram of Gradients (HG) and Histogram of Oriented Gradients (HOG), ExHoG is proposed as a new feature for human detection. ExHoG alleviates the problem of discrimination between a(More)
Unsigned Histogram of Gradients (UHoG) is a popular feature used for human detection. Despite its superior performance as reported in recent literature, an inherent limitation of UHoG is that gradients of opposite directions in a cell are mapped into the same histogram bin. This is undesirable as it will produce the same UHoG feature for two different(More)
Despite superior performance of Local Binary Pattern (LBP) in texture classification and face detection, its performance in human detection has been limited for two reasons. Firstly, LBP differentiates a bright human from a dark background and vice-versa. This increases the intra-class variation of humans. Secondly, LBP is contrast and illumination(More)
Asymmetry in training sets of humans and non-humans and high dimensionality of existing features are problems plaguing human detection. As classification of humans tends to be one class versus all other classes, existing classification methods do not consider this asymmetry in the training sets which leads to sub optimal classifier performance. Furthermore,(More)
In this paper, we present a parts-based modeling framework using Extended Histogram of Gradients (ExHoG) for object detection. Visual object detection is a challenging issue in computer vision where objects need to be detected in varying illumination and contrast environments. Furthermore, objects belonging to the same class exhibit large intra-class(More)
Zebrafish is a useful animal model for studying human diseases such as muscle disorders. However, manual monitoring of fish motion is time-consuming and prone to subjective variations. In this paper, an automatic fish motion analytics framework is proposed. The proposed framework could be exploited to help validate zebrafish models of transgenic zebrafish(More)
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