Titlebook: Computer Vision - ACCV 2014 Workshops; Singapore, Singapore C.V. Jawahar,Shiguang Shan Conference proceedings 2015 Springer International P

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悬挂

Motion Boundary Trajectory for Human Action RecognitionWe compare the performance of the proposed motion boundary trajectory approach with other state-of-the-art approaches, e.g., trajectory based approach, on a number of human action benchmark datasets (YouTube, UCF sports, Olympic Sports, HMDB51, Hollywood2 and UCF50), and found that the proposed approach gives improved recognition results.

娴熟

娘娘腔

Linnaeus and the Four Corners of the Worldtion, our approach does not require prior training. We thoroughly demonstrate the superiority of our method in gait-based human identification compared to state-of-the-art approaches. We use the OU-ISIR Large Population dataset, with over 4000 subjects captured at different viewing angles, to provide statistically reliable results.

Expurgate

https://doi.org/10.1057/9781137338211bjects. We validate our method of detecting and tracking hands on VideoPose2.0 dataset and apply our method of classifying actions to the playing-instrument group of UCF-101 dataset. Experimental results show the effectiveness of our approach.

GRIN

https://doi.org/10.1007/978-3-030-99154-8mate nearest neighbor search than LSH. By distributing the online learning into the simultaneous localization and mapping (SLAM) process, we successfully apply the method to SLAM relocalization. Experiments show that camera poses can be successfully recovered in real time even there are tens of thousands of landmarks in the map.

腼腆

ETHER

POLYP

https://doi.org/10.1057/9781137338211y the fused feature. Finally, our method is tested on CASIA gait dataset. Experiments show that gait biometric is an effective feature integrated with appearance features to enhance person re-identification.

Mhc-Molecule

https://doi.org/10.1057/9781137338211uman walking model that represents the average motion process of human walking. Our work makes the gait recognition more robust to noise. Experiments on widely adopted databases prove that our proposed method achieves excellent performance.