A detection method based on Bayesian hierarchical network for abnormal interaction
Ye Su, JianXin Song
Available Online September 2016.
- https://doi.org/10.2991/amitp-16.2016.66How to use a DOI?
- abnormal interactions, feature exaction, Bayesian hierarchical network.
- Detecting the abnormal human interactions is vital in our daily life, especially when the society pay more attention to public security. But most researches didn't spare enough attention on abnormal interactions. In this paper, salient features are extracted for abnormal interactions, and the amounts of features are reduced to decrease the computation burden. Based on the extracted features, Bayesian hierarchical network is applied to estimating the pose of both persons. Then the corresponding rules for abnormal interaction detection are proposed. Finally, detection results are achieved based on the rules. UT-Interaction dataset is used for experiments. And the results show that the method outperforms with other methods in precision and sensitivity.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Ye Su AU - JianXin Song PY - 2016/09 DA - 2016/09 TI - A detection method based on Bayesian hierarchical network for abnormal interaction BT - Proceedings of the 2016 4th International Conference on Advanced Materials and Information Technology Processing (AMITP 2016) PB - Atlantis Press SP - 333 EP - 340 SN - 2352-538X UR - https://doi.org/10.2991/amitp-16.2016.66 DO - https://doi.org/10.2991/amitp-16.2016.66 ID - Su2016/09 ER -