Cong Geng

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Scale Invariant Feature Transform (SIFT) has shown to be a powerful technique for general object recognition/detection. In this paper, we propose two new approaches: Volume-SIFT (VSIFT) and Partial-Descriptor-SIFT (PDSIFT) for face recognition based on the original SIFT algorithm. We compare holistic approaches: Fisherface (FLDA), the null space approach(More)
This paper proposes a framework of face recognition based on the multi-scale local structures of the face image. While some basic tools in this framework are inherited from the SIFT algorithm, this work investigates and contributes to all major steps in the feature extraction and image matching. New approaches to keypoint detection, partial descriptor and(More)
—A stabilizing observer-based control algorithm for an in-wheel-motored vehicle is proposed, which generates direct yaw moment to compensate for the state deviations. The control scheme is based on a fuzzy rule-based body slip angle (β) observer. In the design strategy of the fuzzy observer, the vehicle dynamics is represented by Takagi–Sugeno-like fuzzy(More)
Face recognition algorithms can be divided into two categories: holistic and local feature-based approaches. Holistic methods are very popular in recent years due to their good performance and high efficiency. However, they depend on careful positioning of the face images into the same canonical pose, which is not an easy task. On the contrary, some local(More)
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