Spatial Object Segmentation Using Stereo Images

TL;DRAbstract

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/).

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