Joint Parsing and Segmentation of Articulated Human Bodies From Videos
- 10.2991/asei-15.2015.21How to use a DOI?
- Human pose; Segmentation; Parsing; Grabcut; Articulated Model
Human body parsing and segmentation are two fundamental problems in computer vision. In this paper we build an automatic system for solving the two problems together. We reconstruct the mixture-of-part model by adding various features, because of the high relevance constructed by the new model, we are able to execute precise parsing inference on the whole human body poses. For segmentation we replace the user interaction input with the detection boxes, since the detection boxes fit the human body part well, it is easy for the refined segmentation to distinguish the foreground and background parts. Experiment results show apparent improvements compared with former methods.
- © 2015, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Zhao Liu AU - Jingrun Sun AU - Chun Chen PY - 2015/05 DA - 2015/05 TI - Joint Parsing and Segmentation of Articulated Human Bodies From Videos BT - Proceedings of the 2015 International conference on Applied Science and Engineering Innovation PB - Atlantis Press SP - 93 EP - 97 SN - 2352-5401 UR - https://doi.org/10.2991/asei-15.2015.21 DO - 10.2991/asei-15.2015.21 ID - Liu2015/05 ER -