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Abstract: this paper, we will focus our attention on the modeling of images and objects through the use of joint histograms. Figure 1 provides an overview diagram of our histogram-based image and object model. More detailed description is given in Section 2. This model has been applied toward image retrieval and object detection in cluttered scenes (Section 4) with promising results (Update)
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BibTeX entry: (Update)
@misc{ merl-mitsubishi,
author = "Http Www Merl",
title = "Mitsubishi Electric Research Laboratories",
url = "citeseer.ist.psu.edu/737937.html" }
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325 Color Indexing (context) - Swain, Ballard - 1991
317 Independent component analysis -- a new concept (context) - Comon - 1994
219 Probabilistic Visual Learning for Object Representation - Moghaddam, Pentland - 1997
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122 Local grayvalue invariants for image retrieval (context) - Schmid, Mohr - 1997
103 Image indexing using color correlograms - Huang, Kumar et al. - 1997
85 Probabilistic Modeling of Local Appearance and Spatial Relat.. (context) - Schneiderman, Kanade - 1998
80 Blind separation of sources (context) - Jutten, Herault - 1991
49 Comparing and evaluating interest points - Schmid, Mohr et al. - 1998
48 A computational approach for corner and vertex detection - Deriche, Giraudon - 1993
18 Columbia Object Image Library: COIL - Nene, Nayar et al. - 1996
14 Object recognition with color cooccurrence histograms (context) - Chang, Krumm - 1999
10 Regionsof -Interest and Spatial Layout in Content-based Imag.. (context) - Moghaddam, Biermann et al. - 1999
2 Introduction to Statistical Patter Recognition (context) - Fukunaga - 1971
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