The work which won the Best Paper Award at CVPR is titled "Putting Objects in Perspective".
Quoting Derek's project description, "Image understanding requires not only individually estimating elements of the visual world but also capturing the interplay among them. We provide a framework for placing local object detection in the context of the overall 3D scene by modeling the interdependence of objects, surface orientations, and camera viewpoint. Most object detection methods consider all scales and locations in the image as equally likely. We show that with probabilistic estimates of 3D geometry, both in terms of surfaces and world coordinates, we can put objects into perspective and model the scale and location variance in the image. Our approach reflects the cyclical nature of the problem by allowing probabilistic object hypotheses to refine geometry and vice-versa. Our framework allows painless substitution of almost any object detector and is easily extended to include other aspects of image understanding."
The slashdot story link(June 14th) can be found here:
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