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http://dx.doi.org/10.5762/KAIS.2012.13.10.4807

Segmentation of Target Objects Based on Feature Clustering in Stereoscopic Images  

Jang, Seok-Woo (Department of Digital Media, Anyang University)
Choi, Hyun-Jun (Department of Electronic Engineering, Mokpo National Maritime University)
Huh, Moon-Haeng (Department of Digital Media, Anyang University)
Publication Information
Journal of the Korea Academia-Industrial cooperation Society / v.13, no.10, 2012 , pp. 4807-4813 More about this Journal
Abstract
Since the existing methods of segmenting target objects from various images mainly use 2-dimensional features, they have several constraints due to the shortage of 3-dimensional information. In this paper, we therefore propose a new method of accurately segmenting target objects from three dimensional stereoscopic images using 2D and 3D feature clustering. The suggested method first estimates depth features from stereo images by using a stereo matching technique, which represent the distance between a camera and an object from left and right images. It then eliminates background areas and detects foreground areas, namely, target objects by effectively clustering depth and color features. To verify the performance of the proposed method, we have applied our approach to various stereoscopic images and found that it can accurately detect target objects compared to other existing 2-dimensional methods.
Keywords
Feature Clustering; Stereoscopic Images; Target Object; Disparity Map; Stereo Matching Algorithm;
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Times Cited By KSCI : 3  (Citation Analysis)
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