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Issue No.11 - November (2011 vol.33)
pp: 2147-2159
Daniel Neilson , University of Saskatchewan, Saskatoon and University of Alberta, Edmonton
Yee-Hong Yang , University of Alberta, Edmonton
ABSTRACT
Match cost functions are common elements of every stereopsis algorithm that are used to provide a dissimilarity measure between pixels in different images. Global stereopsis algorithms incorporate assumptions about the smoothness of the resulting distance map that can interact with match cost functions in unpredictable ways. In this paper, we present a large-scale study on the relative performance of a structured set of match cost functions within several global stereopsis frameworks. We compare 272 match cost functions that are built from component parts in the context of four global stereopsis frameworks with a data set consisting of 57 stereo image pairs at three different variances of synthetic sensor noise. From our analysis, we infer a set of general rules that can be used to guide derivation of match cost functions for use in global stereopsis algorithms.
INDEX TERMS
Stereopsis, stereo matching, stereo correspondence, global algorithms, match cost functions.
CITATION
Daniel Neilson, Yee-Hong Yang, "A Component-Wise Analysis of Constructible Match Cost Functions for Global Stereopsis", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol.33, no. 11, pp. 2147-2159, November 2011, doi:10.1109/TPAMI.2011.67
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