Scene-driven Cues for Viewpoint Classification for Elongated Object Classes
In Proceedings British Machine Vision Conference 2014
AbstractIn this paper we present a top-down, scene-driven, approach to classify the viewpoint of elongated objects. Viewpoint classification is achieved based on the correspondence between the image evidence acquired by a detector on one hand, and bounding boxes of object proposals generated from scene consistent cues on the other hand. We explore several methods to generate scene-driven proposals: first, by generating object proposals in the 3D scene and, using the ground plane, projecting them to the image space, and second, by sampling objects from a history set of objects previously seen with the same camera setup in the scene. Experiments on the challenging KITTI dataset show the performance of the proposed method for viewpoint classification for controlled-camera applications such as autonomous navigation.
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