Multi view semantic temporal video segmentation
In this work, we propose a multi view temporal video segmentation approach that employs a Gaussian scoring process for determining the best segmentation positions. By exploiting the semantic action information that the dense trajectories video description offers, this method can detect intra shot actions as well, unlike shot boundary detection approaches. We compare the temporal segmentation results of the proposed method to both single view and multi view methods, and also compare the action recognition results obtained on ground truth video segments to the ones obtained on the proposed multi view segments, on the IMPART multi view action data set.
2016 IEEE International Conference on Image Processing (ICIP)