Pose-invariant kinematic features for action recognition
Recognition of actions from videos is a difficult task due to several factors like dynamic backgrounds, occlusion, pose-variations observed. To tackle the pose variation problem, we propose a simple method based on a novel set of pose-invariant kinematic features which are encoded in a human body ce...
Saved in:
Main Authors: | Ramanathan, Manoj, Yau, Wei-Yun, Teoh, Eam Khwang, Thalmann, Nadia Magnenat |
---|---|
Other Authors: | School of Electrical and Electronic Engineering |
Format: | Conference or Workshop Item |
Language: | English |
Published: |
2020
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/138068 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Mutually reinforcing motion-pose framework for pose invariant action recognition
by: Ramanathan, Manoj, et al.
Published: (2020) -
Combining pose-invariant kinematic features and object context features for RGB-D action recognition
by: Ramanathan, Manoj, et al.
Published: (2019) -
An analytic gabor feedforward network for single-sample and pose-invariant face recognition
by: Oh, Beom-Seok, et al.
Published: (2019) -
Deformable pose traversal convolution for 3D action and gesture recognition
by: Weng, Junwu, et al.
Published: (2020) -
Handling pose variation in face recognition using SIFT
by: Bhattacharya, B., et al.
Published: (2014)