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|Title||Video-based person re-identification|
Person Re-ID in multi-camera surveillance system has been researched increasingly in recent years due to its presence in numerous important applications, such as surveillance, forensics, smart environments, multimedia applications, and so on . It is a problem of person identity association across camera views at different locations and times. Most of the reported person
Re-ID methods deal with one sole image and the manually extracted human ROIs (Region of Interest) . Therefore, rich information containing in image sequence (video) is still under-exploited. Moreover, when working with automatic ROI detection, we have to face to two open issues of object detection: miss detection and false positive. Recently, deep learning has been applied for video-based person re-identification . The main aim of this work is to investigate deeply the use of deep learning for video-based person re-identification.
- Study person re-identification
- Study different deep learning architecture for person re-identification.
- Propose suitable framework for person re-identification based on deep learning
- Evaluate the proposed method in available datasets such as MARS dataset
This subject is dedicated to Vietnamese students as well as foreigner. The students who have a fairly good knowledge about computer vision, image processing and deep learning are privileged.
 A. Bedagkar-Gala, S. K. Shah, A survey of approaches and trends in person re-identification, Image and Vision Computing 32 (4) (2014) 270-286.
 Thanh-Thuy Pham, Thi-Lan Le, Trung-Kien Dao, Duy-Hung Le, A robust model for person re-identification in multimodal person localization, in The Ninth International Conference on Mobile Ubiquitous Computing, Systems, Services and Technologies (UBICOMM 2015), 2015, p. 51
 Lin Wu, Chunhua Shen, Anton van den Hengel, Convolutional LSTM Networks for Video-based Person Re-identification, 2016.