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Object detection with geometrical context feedback loop
Conference paper

Object detection with geometrical context feedback loop

Min Sun, Sid Ying-Ze Bao and Silvio Savarese
British Machine Vision Conference, BMVC 2010 - Proceedings
2010

Abstract

We propose a new coherent framework for joint object detection, 3D layout estimation, and object supporting region segmentation from a single image. Our approach is based on the mutual interactions among three novel modules: i) object detector; ii) scene 3D layout estimator; iii) object supporting region segmenter. The interactions between such modules capture the contextual geometrical relationship between objects, the physical space including these objects, and the observer. An important property of our algorithm is that the object detector module is capable of adaptively changing its confidence in establishing whether a certain region of interest contains an object (or not) as new evidence is gathered about the scene layout. This enables an iterative estimation procedure where the detector becomes more and more accurate as additional evidence about a specific scene becomes available. Extensive quantitative and qualitative experiments are conducted on a new in-house dataset [1] and two publicly available datasets [17, 25], and demonstrate competitive object detection, 3D layout estimation, and object supporting region segmentation results. © 2010. The copyright of this document resides with its authors.

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