Object Segmentation based on Saliency Extraction and Bounding Box

DOI

10.2991/lemcs-14.2014.130How to use a DOI?

Keywords

object segmentation; saliency extraction; graph cuts; bounding box; adaptive weight

Abstract

Object segmentation is desirable in many practical applications, e.g., object classification. However, due to various object appearances and shapes, confusing backgrounds, object segmentation in an effective way is still a challenging issue. In this paper, a novel algorithm of object segmentation based on saliency extraction and bounding boxes is proposed. The segmentation performance is significantly improved by introducing saliency extraction into the segmentation scheme. Firstly, bounding boxes are acquired by object detection algorithms, foreground and background model is constructed using bounding boxes. Then, saliency extraction procedure is introduced, and adaptive weights for each pixel are computed based on the saliency extraction. Finally, undirected graph which incorporates the adaptive weights for each pixel is constructed and graph cuts is implemented to obtain the segmentation results. Comprehensive and comparative experiments demonstrate that our proposed algorithm has achieved promising performance over a challenging public available dataset.

Copyright

© 2014, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Jian Ma
AU  - Lei Huang
AU  - Bo Yin
AU  - Fengfu Yin
PY  - 2014/05
DA  - 2014/05
TI  - Object Segmentation based on Saliency Extraction and Bounding Box
BT  - Proceedings of the International Conference on Logistics, Engineering, Management and Computer Science
PB  - Atlantis Press
SP  - 566
EP  - 570
SN  - 1951-6851
UR  - https://doi.org/10.2991/lemcs-14.2014.130
DO  - 10.2991/lemcs-14.2014.130
ID  - Ma2014/05
ER  -