Keyang Cheng

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Searching for specific persons from surveillance videos captured by different cameras, known as person re-identification, is a key yet under-addressed challenge. Difficulties arise from the large variations of human appearance in different poses, and from the different camera views that may be involved, making low-level descriptor representation unreliable.(More)
To overcome the disadvantage of classical recognition model which cannot perform enough well when there are some noises or lost frames in expression image sequencers, a novel model called Burial Markov Model is applied in facial expression recognition based on video image sequences. Compared with Hidden Markov model, Buried Markov Model (BMM), as an(More)
The paper presents a new algorithm of pedestrian detection based on efficient fused lasso algorithm (EFLA) and analyses the sparse representation framework. The method considers the structure information of pedestrian image and makes it encoded into the sparse representation model to obtain good discrimination. The proposed algorithm makes use of EFLA to(More)
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