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By Tomasz J. Malisiewicz, Alexei A. Efros and Jonathan C. Huang


We present an object detection system and show results on the PASCAL 2006 dataset. We introduce a codebook defined over segment-level features and show how multiple segmentations and Latent Topic Models can be used to localize objects in images despite the bag-of-words assumption. We demonstrate how to train both the Latent Dirichlet Allocation model and the Correlated Topic Model in a supervised way and show how our approach is capable of detecting multiple instances of objects in images such as cars, horses, grass, sheep, etc.

Year: 2009
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