Fine-Grained Pose Temporal Memory Module for Video Pose Estimation and Tracking

Chaoyi Wang, Yang Hua, Tao Song, Zhengui Xue, Ruhui Ma, Neil Robertson, Haibing Guan

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

Abstract

The task of video pose estimation and tracking has been largely improved with the development of image pose estimation recently. However, there are still many challenging cases, such as body part occlusion, fast body motion, camera zooming, and complex background. Most existing methods generally use the temporal information to get more precise human bounding boxes or just use it in the tracking stage, but they fail to improve the accuracy of pose estimation tasks. To better solve these problems and utilize the temporal information efficiently and effectively, we present a novel structure, called pose temporal memory module, which is flexible to be transferred into top-down pose estimation frameworks. The temporal information stored in the pose temporal memory is aggregated into the current frame feature in our proposed module. We also transfer compositional de-attention (CoDA) to solve the unique keypoint occlusion problem in this task and propose a novel keypoint feature replacement to recover the extreme error detection under fine-grained keypoint-level guidance. To verify the generality and effectiveness of our proposed method, we integrate our module into two widely used pose estimation frameworks and obtain notable improvement on the PoseTrack dataset with only a few extra computing resources.
Original languageEnglish
Title of host publication2021 IEEE International Conference on Acoustics, Speech and Signal Processing: Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)978-1-7281-7605-5
ISBN (Print)978-1-7281-7606-2
DOIs
Publication statusPublished - 13 May 2021
EventIEEE International Conference on Acoustics, Speech, and Signal Processing 2021 - Online, Toronto, Canada
Duration: 06 Jun 202111 Jun 2021
https://2021.ieeeicassp.org/

Publication series

NameIEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
ISSN (Print)1520-6149
ISSN (Electronic)2379-190X

Conference

ConferenceIEEE International Conference on Acoustics, Speech, and Signal Processing 2021
Abbreviated titleICASSP 2021
Country/TerritoryCanada
CityToronto
Period06/06/202111/06/2021
Internet address

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