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An Iterative Image Registration Technique with an Application to Stereo Vision

An Iterative Image Registration Technique with an Application to Stereo Vision,Bruce D. Lucas,Takeo Kanade

An Iterative Image Registration Technique with an Application to Stereo Vision   (Citations: 3231)
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Image registration finds a variety of applications in computer vision. Unfortunately, traditional image registration techniques tend to be costly. We present a new image registration technique that makes use of the spatial intensity gradient of the images to find a good match using a type of Newton-Raphson iteration. Our technique is taster because it examines far fewer potential matches between the images than existing techniques Furthermore, this registration technique can be generalized to handle rotation, scaling and shearing. We show how our technique can be adapted tor use in a stereo vision system.
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    • ...We developed two analysis algorithms. The first determines the average velocity of the moving contours inside each well. This algorithm derives the velocity from the optical flow vectors of the luminance component of the video stream from a pair of adjacent frames approximately 100 ms apart. The algorithm uses the sparse iterative version of the Lucas-Kanade optical flow in pyramids provided with the OpenCV framework ...

    Chris Marcellinoet al. WormAssay: A Novel Computer Application for Whole-Plate Motion-based S...

    • ...Lucas and Kanade (1981) assumed a constant motion within a given neighbourhood, NH, around each pixel...

    Martin Gadeet al. Mesoscale surface current fields in the Baltic Sea derived from multi-...

    • ...This tracker allows facilitators to choose the region of interest (small blue square in <0002" ref-type="fig">Figure 2 where fine motion is extracted using optical flow; Lucas & Kanade, 1981)...

    Cesar Mauriet al. A Nonformal Interactive Therapeutic Multisensory Environment for Peopl...

    • ...In this paper we present GPU-KLT, a GPU-based implementation for the popular KLT feature tracker [6,7] and GPU-SIFT, a GPU-based implementation for the SIFT feature extraction algorithm [10]...
    • ...The KLT tracking algorithm [6,7] computes displacement of features or interest points between consecutive video frames when the image brightness constancy constraint is satisfied and image motion is fairly small...
    • ...It is evaluated over the complete image [6,7] and a subsequent non-maximal suppression is performed...

    Sudipta N. Sinhaet al. Feature tracking and matching in video using programmable graphics har...

    • ...These algorithms are applicable to problems with fewer parameters such as the Lucas-Kanade algorithm (Lucas and Kanade 1981) and variants (Le Besnerais and Champagnat 2005), which solve for a single flow vector (2 unknowns) independently for each block of pixels...
    • ...The most common approach is to build image pyramids by repeated blurring and downsampling (Lucas and Kanade 1981; Glazer et al. 1983 ;B urt et al.1983; Enkelman 1986; Anandan 1989; Black and Anandan 1996; Battiti et al. 1991; Bruhn et al. 2005)...
    • ...Algorithms such as Jung et al. (2008), Lempitsky et al. (2008) and Trobin et al. (2008) assume that a number of candidate flow fields have been generated by running standard algorithms such as Lucas and Kanade (1981), and Horn and Schunck (1981), possibly multiple times with a number of different parameters...
    • ...Dynamic MRF (Glocker et al. 2008) 366 Pyramid LK (Lucas and Kanade 1981) 11.9...

    Simon Bakeret al. A Database and Evaluation Methodology for Optical Flow

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