Abstract We propose a new framework for human action localization in video sequences. The option to not only detect but also localize actions in surveillance video is crucial to improving system's ability to manage high volumes of CCTV. In the approach, the action localization task is formulated the maximum-path finding problem in the directed spatio-temporal video-graph. The graph is constructed on the top of frame and temporal-based low-level features. To localize actions in the video-graph, we apply a maximum-path algorithm to find the path in the graph that is considered to be the localized action in the video. The proposed approach achieves competitive performance with the J-HMDB and the UCF-Sports dataset.

Url http://doras.dcu.ie/21832/1/Camera_ready_AVSS_2017.pdf

Collections Ireland -> Dublin City University -> Publication Type = Conference or Workshop Item
Ireland -> Dublin City University -> DCU Faculties and Centres = DCU Faculties and Schools: Faculty of Engineering and Computing: School of Computing
Ireland -> Dublin City University -> Status = Published
Ireland -> Dublin City University -> DCU Faculties and Centres = Research Initiatives and Centres: INSIGHT Centre for Data Analytics
Ireland -> Dublin City University -> Subject = Computer Science: Machine learning