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We presented an application of SURF operator and epipolar constraint for stereo matching of binocular citrus images. First, R-B space images were achieved by linear transform of original images' color space. Second, fast Hessian-matrix detector was used to detect the interest points and the SURF descriptor was used to describe the points' features. Finally, Euclidean distance and the epipolar constraint...
In this paper, we propose a method for projecting images onto non-planar screens by using projector-camera systems eliminating distortion in projected images. In this system, point-to-point correspondences in a projector image and a camera image should be extracted. For finding correspondences, the epipolar geometry between a projector and a camera is used. By using dynamic programming method on epipolar...
This paper presents a new algorithm for automatically measuring fire spreading characteristics by means of a stereovision system. The proposed framework is based on the use of a pre-calibrated trinocular stereo camera. The first and second steps permit the segmentation and features detection in the images. The third step is a stereo matching approach used in order to automatically process successive...
Road detection is a vital task for the development of autonomous vehicles. The knowledge of the free road surface ahead of the target vehicle can be used for autonomous driving, road departure warning, as well as to support advanced driver assistance systems like vehicle or pedestrian detection. Using vision to detect the road has several advantages in front of other sensors: richness of features,...
This paper presents region moments, a class of appearance descriptors based on image moments applied to a pool of image features. A careful design of the moments and the image features, makes the descriptors scale and rotation invariant, and therefore suitable for vehicle detection from aerial video, where targets appear at different scales and orientations. Region moments are linearly related to...
A novel method is proposed for the problem of frame-to-frame correspondence search in video sequences. The method, based on hashing of low-dimensional image descriptors, establishes dense correspondences and allows large motions. All image pixels are considered for matching, the notion of interest points is reviewed. In our formulation, points of interest are those that can be reliably matched. Their...
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