Object discovery on RGB-D data via salient object proposals
Wanyi Li, Peng Wang, Hong Qiao, Naiji Fan, Hai Zhou, Jing Feng · 2015
This paper presents an effective approach for object discovery in which both object proposals and saliency information are exploited. Our algorithm consists of three basic steps. Firstly, a set of object proposals are generated. Secondly, a saliency map is calculated and salient blobs are detected on the calculated saliency map. Finally, a saliency integrated objectness measure is proposed to rank object proposals thus objects are discovered. Experiments on a dataset of object discovery demonstrate the effectiveness of the proposed method.