Context-aware deep feature compression for high-speed visual tracking

Jongwon Choi, Hyung Jin Chang, Tobias Fischer, Sangdoo Yun, Kyuewang Lee, Jiyeoup Jeong, Yiannis Demiris, Jin Young Choi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

110 Citations (Scopus)
184 Downloads (Pure)

Abstract

We propose a new context-aware correlation filter based tracking framework to achieve both high computational speed and state-of-the-art performance among real-time trackers. The major contribution to the high computational speed lies in the proposed deep feature compression that is achieved by a context-aware scheme utilizing multiple expert auto-encoders; a context in our framework refers to the coarse category of the tracking target according to appearance patterns. In the pre-training phase, one expert auto-encoder is trained per category. In the tracking phase, the best expert auto-encoder is selected for a given target, and only this auto-encoder is used. To achieve high tracking performance with the compressed feature map, we introduce extrinsic denoising processes and a new orthogonality loss term for pre-training and fine-tuning of the expert autoencoders. We validate the proposed context-aware framework through a number of experiments, where our method achieves a comparable performance to state-of-the-art trackers which cannot run in real-time, while running at a significantly fast speed of over 100 fps.
Original languageEnglish
Title of host publicationProceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2018)
PublisherIEEE Computer Society
Number of pages10
ISBN (Electronic)9781538664209
DOIs
Publication statusPublished - 17 Dec 2018
EventIEEE Conference on Computer Vision and Pattern Recognition (CVPR 2018) - Salt Lake City, United States
Duration: 18 Jun 201822 Jun 2018

Publication series

NameProceedings (IEEE Computer Society Conference on Computer Vision and Pattern Recognition)
PublisherIEEE
ISSN (Electronic)2575-7075

Conference

ConferenceIEEE Conference on Computer Vision and Pattern Recognition (CVPR 2018)
Country/TerritoryUnited States
CitySalt Lake City
Period18/06/1822/06/18

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