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A simple stereo matching algorithm is proposed that visits only a small fraction of disparity space in order to find a semi-dense disparity map. It works by growing from a small set of correspondence seeds. Unlike in known seed-growing algorithms, it guarantees matching accuracy and correctness, even in the presence of repetitive patterns. This success is(More)
In many retrieval, object recognition, and wide-baseline stereo methods, correspondences of interest points (distinguished regions) are commonly established by matching compact descriptors such as SIFTs. We show that a subsequent cosegmentation process coupled with a quasi-optimal sequential decision process leads to a correspondence verification procedure(More)
Continuous action recognition is more challenging than isolated recognition because classification and segmentation must be simultaneously carried out. We build on the well known dynamic time warping framework and devise a novel visual alignment technique, namely dynamic frame warping (DFW), which performs isolated recognition based on per-frame(More)
A gram-positive, slowly growing rod effectively utilizing morpholine as the sole source of organic carbon, nitrogen, and energy was isolated from a mixed culture in a laboratory reactor. The strain was tentatively identified as Mycobacterium aurum. Its growth characteristics at 20 degrees C and pH 6.5 were as follows: maximum specific growth rate, 0.052(More)
3D Shape matching is an important problem in computer vision. One of the major difficulties in finding dense correspondences between 3D shapes is related to the topological discrepancies that often arise due to complex kinematic motions. In this paper we propose a shape matching method that is robust to such changes in topology. The algorithm starts from a(More)
The combination of range sensors with color cameras can be very useful for robot navigation, semantic perception, manipulation, and telepresence. Several methods of combining range- and color-data have been investigated and successfully used in various robotic applications. Most of these systems suffer from the problems of noise in the range-data and(More)
The knowledge of stereo matching algorithm properties and behaviour under varying conditions is crucial for the selection of a proper method for the desired application. In this paper we study the behaviour of four representative matching algorithms under varying signal-to-noise ratio in six types of error statistics. The errors are focused on basic(More)
In stereo literature, there is no standard method for evaluating algorithms for semi-dense stereo matching. Moreover, existing evaluations for dense methods require a fixed parameter setting for the tested algorithms. In this paper, we propose a method that overcomes these drawbacks and still is able to compare algorithms based on a simple numerical value,(More)