TY - GEN
T1 - Online pedestrian tracking with multi-stage re-identification
AU - Jiang, Yi Fan
AU - Shin, Hyunhak
AU - Ju, Jaeyong
AU - Ko, Hanseok
N1 - Funding Information:
Acknowledgements: This work was supported by the ONRG grant: N62909-16-1-2185. This work was sup- ported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (No. 2017R1A2B4012720). This subject is supported by Korea Ministry of Environment (MOE) as Public Technology Program based on Environmental Policy.
PY - 2017/10/20
Y1 - 2017/10/20
N2 - Nowadays the task of tracking pedestrians is often addressed within a tracking-by-detection framework, which in most cases entails that the position of each target has been detected before tracking begins. However in some cases, a pedestrian who is being tracked may be obscured by other targets or obstacles, and during this period they may change their trajectory or speed (track drift), and sometimes such a target may leave the FOV (Field of View) [10] but appear again later. These temporary disappearances and absence of detections disrupt the work of the detectors to such an extent that there is a significant decline in performance. In this paper, we propose a novel approach to pedestrian tracking based on multi-stage re-identification. To deal with the problems discussed above, the proposed framework is comprised of a two-stage re-identification algorithm dealing with cases of track drift and re-entry into the FOV individually, in order to match the identities of lost and reappeared targets through a comparison of the affinities between their appearance, size and position, and also to update the status of re-identified targets through this assessment. The experimental results demonstrate that this framework can effectively handle complex temporary lost and re-entry situations with robustness, and that its performance is state of the art.
AB - Nowadays the task of tracking pedestrians is often addressed within a tracking-by-detection framework, which in most cases entails that the position of each target has been detected before tracking begins. However in some cases, a pedestrian who is being tracked may be obscured by other targets or obstacles, and during this period they may change their trajectory or speed (track drift), and sometimes such a target may leave the FOV (Field of View) [10] but appear again later. These temporary disappearances and absence of detections disrupt the work of the detectors to such an extent that there is a significant decline in performance. In this paper, we propose a novel approach to pedestrian tracking based on multi-stage re-identification. To deal with the problems discussed above, the proposed framework is comprised of a two-stage re-identification algorithm dealing with cases of track drift and re-entry into the FOV individually, in order to match the identities of lost and reappeared targets through a comparison of the affinities between their appearance, size and position, and also to update the status of re-identified targets through this assessment. The experimental results demonstrate that this framework can effectively handle complex temporary lost and re-entry situations with robustness, and that its performance is state of the art.
UR - http://www.scopus.com/inward/record.url?scp=85039911919&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85039911919&partnerID=8YFLogxK
U2 - 10.1109/AVSS.2017.8078505
DO - 10.1109/AVSS.2017.8078505
M3 - Conference contribution
AN - SCOPUS:85039911919
T3 - 2017 14th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2017
BT - 2017 14th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 14th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2017
Y2 - 29 August 2017 through 1 September 2017
ER -