Efficient search of Top-K video subvolumes for multi-instance action detection

Action detection was formulated as a subvolume mutual information maximization problem in [8], where each subvolume identifies where and when the action occurs in the video. Despite the fact that the proposed branch-and-bound algorithm can find the best subvolume efficiently for low resolution videos, it is still not efficient enough to perform multiinstance detection in videos of high spatial resolution. In this paper we develop an algorithm that further speeds up the subvolume search and targets on real-time multi-instance action detection for high resolution videos (e.g. 320 × 240 or higher). Unlike the previous branch-and-bound search technique which restarts a new search for each action instance, we find the Top-K subvolumes simultaneously with a single round of search. To handle the larger spatial resolution, we downsample the volume of videos for a more efficient upperbound estimation. To validate our algorithm, we perform experiments on a challenging dataset of 54 video...

• Type: Conference
• Year: 2010
• Where: ICMCS
• Authors: Norberto A. Goussies, Zicheng Liu, Junsong Yuan
• Keywords: Action Detection, ICMCS 2010, Multimedia, Resolution Videos, Spatial Resolution