標題: RGBD Salient Object Detection using Spatially Coherent Deep Learning Framework
作者: Huang, Posheng
Shen, Chin-Han
Hsiao, Hsu-Feng
資訊工程學系
Department of Computer Science
關鍵字: fully convolutional networks;salient object detection;deep learning
公開日期: 1-Jan-2018
摘要: In this paper, a learning based salient object detection method for RGBD images is introduced. With the assistance of depth information, the silhouette features of an object can be retrieved primarily, and it can lead to better detection of salient objects. In addition, many recent works still rely on some image post-processing methods to improve their performance. We develop a more efficient end-to-end model with a modified design of loss function used in our training network. The design of the new loss function is to increase the spatial coherence of detected salient objects. From the evaluation results, the proposed approach shows good performance compared with the methods that are considered to be state-of-the-art.
URI: http://hdl.handle.net/11536/151059
ISSN: 1546-1874
期刊: 2018 IEEE 23RD INTERNATIONAL CONFERENCE ON DIGITAL SIGNAL PROCESSING (DSP)
Appears in Collections:Conferences Paper