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Manual annotation of rodent behaviors in video is time-consuming. By learning a classifier, we can automate the labeling process. Still, this strategy requires a sufficient number of labeled examples. Moreover, we need to train new classifiers when there is a change in the set of behaviors that we consider or in the manifestation of these behaviors in video. Consequently, there is a need for an efficient...
Depth sensors based on projected structured light have become standard in robotics research. However, when several of these sensors share the same workspace, the measurement quality can deteriorate significantly due to interference of the projected light patterns. We present a comprehensive study of this effect in Kinect and Xtion RGB-D sensors. In particular, our study investigates the effect of...
We propose a novel method for object search in realistic environments. We formalize object search as a probabilistic inference problem over possible object locations. The method makes two contributions. First, we identify five priors, each capturing structure inherent to the physical world that is relevant to the search problem. Second, we propose a formalization of the object search problem that...
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