Mining actionlet ensemble for action recognition with depth cameras
Human action recognition is an important yet challenging task. The recently developed commodity depth sensors open up new possibilities of dealing with this problem but also present some unique challenges. The depth maps captured by the depth cameras are very noisy and the 3D positions of the tracke...
Saved in:
Main Authors: | Wang, Jiang, Liu, Zicheng, Wu, Ying, Yuan, Junsong |
---|---|
Other Authors: | School of Electrical and Electronic Engineering |
Format: | Conference or Workshop Item |
Language: | English |
Published: |
2013
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/100602 http://hdl.handle.net/10220/17897 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Recognizing and predicting human actions with depth camera
by: Weng, Junwu
Published: (2020) -
Discriminative video pattern search for efficient action detection
by: Yuan, Junsong, et al.
Published: (2013) -
Propagative Hough voting for human activity recognition
by: Yu, Gang, et al.
Published: (2013) -
Mining visual collocation patterns via self-supervised subspace learning
by: Yuan, Junsong, et al.
Published: (2013) -
Action-stage emphasized spatiotemporal VLAD for video action recognition
by: Tu, Zhigang, et al.
Published: (2021)