Abstract
This paper presents a technique to determine the identity of objects in a scene using histograms of the responses of a vector of local linear neighborhood operators (receptive fields). This technique can be used to determine the most probable objects in a scene, independent of the object's position, image-plane orientation and scale. In this paper we describe the mathematical foundations of the technique and present the results of experiments which compare robustness and recognition rates for different local neighborhood operators and histogram similarity measurements.
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© 1996 Springer-Verlag Berlin Heidelberg
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Schiele, B., Crowley, J.L. (1996). Object recognition using multidimensional receptive field histograms. In: Buxton, B., Cipolla, R. (eds) Computer Vision — ECCV '96. ECCV 1996. Lecture Notes in Computer Science, vol 1064. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0015571
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DOI: https://doi.org/10.1007/BFb0015571
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