PT Journal
AU Rahma Kalboussi
   Aymen Azaza
   Joost Van de Weijer
   Mehrez Abdellaoui
   Ali Douik
TI Object proposals for salient object segmentation in videos
SO Multimedia Tools and Applications
JI MTAP
PY 2020
BP 8677
EP 8693
VL 79
IS 13
AB Salient object segmentation in videos is generally broken up in a video segmentation part and a saliency assignment part. Recently, object proposals, which are used to segment the image, have had significant impact on many computer vision applications, including image segmentation, object detection, and recently saliency detection in still images. However, their usage has not yet been evaluated for salient object segmentation in videos. Therefore, in this paper, we investigate the application of object proposals to salient object segmentation in videos. In addition, we propose a new motion feature derived from the optical flow structure tensor for video saliency detection. Experiments on two standard benchmark datasets for video saliency show that the proposed motion feature improves saliency estimation results, and that object proposals are an efficient method for salient object segmentation. Results on the challenging SegTrack v2 and Fukuchi benchmark data sets show that we significantly outperform the state-of-the-art.
ER