Model Based Correspondence
نویسندگان
چکیده
We present a new technique to register an object model with an observed image. The technique uses the model to establish an image-to-model correspondence and, therefore, to facilitate the registration process. The model guides and constrains the matching procedure in order to reduce the inherent complexity of the registration problem and to increase the robustness and eeciency of the solution. The technique begins by roughly aligning the image and model using an overall aane transformation. It then determines correspondence estimates between a sparse set of model and image contours. The major contribution of the approach is that the technique is able to constrain the rest of the matches via global information from the model. This process can be repeated to reene the resulting correspondence. We have incorporated our technique into the linear combination object recognition scheme and have tested the entire system successfully on a variety of objects. There are three beneets to our approach. First, it is eeective; experiments show that our procedure quickly converges to a solution, if one exists. Second, it is computationally simple and eecient; the use of models eeectively constrains the matches and the process results in a linear solution. Finally, the procedure is robust; moderate errors in the rough alignment stage do not impair the subsequent correspondence procedure.
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تاریخ انتشار 1995