Unsupervised learning of object features from video sequences

We develop an efficient algorithm for unsupervised learning of object models as constellations of features, from low resolution video sequences. The input images typically contain single or multiple objects that change in pose, scale and degree of occlusion. Also, the objects can move significantly...

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Bibliographic Details
Published in2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) Vol. 1; pp. 1142 - 1149 vol. 1
Main Authors Leordeanu, M., Collins, R.
Format Conference Proceeding
LanguageEnglish
Published IEEE 2005
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