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High-level vision applications often incorporate image segmentation techniques into their preprocessing stages to reduce image data and to improve overall execution efficiency. Traditional segmentation approaches often focus on creating homogenous, connected regions of pixels to roughly correspond with image object boundaries. These methods tend to blend or remove important image details and are often...
Piecewise planar models for stereo have recently become popular for modeling indoor and urban outdoor scenes. The strong planarity assumption overcomes the challenges presented by poorly textured surfaces, and results in low complexity 3D models for rendering, storage, and transmission. However, such a model performs poorly in the presence of non-planar objects, for example, bushes, trees, and other...
Many practical applications in the field of medical image processing need valid, reliable and fast image segmentation. In this study, we propose a semi-automatic segmentation approach. In this approach, an extended version of the Otsu's method for three level thresholding and a recursive connected component algorithm are combined. The segmentation process is accomplished using Extended Otsu's method...
Most approaches to vehicle tracking have adopted a single calibrated camera for the task, which leads to an under-conditioned problem. We present a surveillance system for on-line vehicle tracking based on two cameras and structure from motion (SfM). Our surveillance system starts by tracking feature points. A novel matching scheme is proposed that allows a subset of feature points to be corresponded...
Indoor and outdoor urban environments posses many regularities which can be efficiently exploited and used for general image parsing tasks. We present a novel approach for detecting rectilinear structures and demonstrate their use for wide baseline stereo matching, planar 3D reconstruction, and computation of geometric context. Assuming a presence of dominant orthogonal vanishing directions, we proceed...
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