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In this paper, we propose a new local descriptor for action recognition in depth images. The proposed descriptor relies on surface normals in 4D space of depth, time, spatial coordinates and higher-order partial derivatives of depth values along spatial coordinates. In order to classify actions, we follow the traditional Bag-of-words (BoW) approach, and propose two encoding methods termed Multi-Scale...
This paper aims to study the problem of spoofing attack detection for facial recognition systems. Real faces and falsified faces present in front of a security system (phone's camera in our case) have differences of micro-textures on their surface, which are exploited to discriminate face spoofing images. Our method exploits the statistic behavior of the distribution of noise's local variances, which...
In this paper, we propose a new local descriptor for action recognition in depth images. Our proposed descriptor jointly encodes the shape and motion cues using surface normals in 4D space of depth, time, spatial coordinates and higher-order partial derivatives of depth values along spatial coordinates. In a traditional Bag-of-words (BoW) approach, local descriptors extracted from a depth sequence...
Among many texture descriptors, the LBP-based representation emerged as an attractive approach thanks to its low complexity and effectiveness. Many variants have been proposed to deal with several limitations of the basic approach like the small spatial support or the noise sensitivity. This paper presents a new method to construct an effective texture descriptor addressing those limitations by combining...
A new descriptor called Multi-modal Binary Patterns (MMBP) is proposed for face recognition. It balances well important requirements for real-world applications, including the robustness, discriminative power, and the low computational cost. The proposed algorithm has several desirable properties: 1) it captures information from face image in any direction as it is oriented feature, 2) being a spatial...
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