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JACIII Vol.14 No.6 pp. 645-653
doi: 10.20965/jaciii.2010.p0645
(2010)

Paper:

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Spatial Object Segmentation Using Stereo Images

Yong Hao*, Lifeng He**, Tsuyoshi Nakamura*,
Yuyan Chao***, and Hidenori Itoh*

*Department of Computer Science and Engineering, Nagoya Institute of Technology, Gokiso-cho, Showa-ku, Nagoya, Aichi 466-8555, Japan

**Graduate School of Information Science and Technology, Aichi Prefectural University, Nagakute-cho, Aichi 480-1198, Japan

***Graduate School of Environment Management, Nagoya Sangyo University, Owariasahi-city, Aichi 488-8711, Japan

Received:
January 23, 2010
Accepted:
July 15, 2010
Published:
September 20, 2010
Creative Commons License
Keywords:
object segmentation, image segmentation, stereo image, minimum spanning tree clustering
Abstract
The framework of our proposed for segmenting objects using spatial location information from stereo images. An efficient graph-based image segmentation algorithm within this framework for combining changes in optical features and physical location to segment reality scenes into perceptually and semantically uniform regions. Optical and physical location are extracted using k-means clustering, and we propose a rules table for combining optical and spatial features together. The performance of our proposed framework is demonstrated in a series of reality-scene images using experimental data from the Middlebury stereo image data
(http://vision.middlebury.edu/stereo/data/).
Cite this article as:
Y. Hao, L. He, T. Nakamura, Y. Chao, and H. Itoh, “Spatial Object Segmentation Using Stereo Images,” J. Adv. Comput. Intell. Intell. Inform., Vol.14 No.6, pp. 645-653, 2010.
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Last updated on Dec. 01, 2023