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Bag-of-words (BoW) methods are a popular class of object recognition methods that use image features (e.g., SIFT) to form visual dictionaries and subsequent histogram vectors to represent object images in the recognition process. The accuracy of the BoW classifiers, however, is often limited by the presence of uninformative features extracted from the(More)
We propose an efficient distributed object recognition system for sensing, compression, and recognition of 3-D objects and landmarks using a network of wireless smart cameras. The foundation is based on a recent work that shows the representation of scale-invariant image features exhibit certain degree of sparsity: If a common object is observed by multiple(More)
Smart camera networks have recently emerged as a new class of sensor network infrastructure that is capable of supporting high-power in-network signal processing and enabling a wide range of applications. In this article, we provide an exposition of our efforts to build a low-bandwidth wireless camera network platform, called CITRIC, and its applications in(More)
After the three DARPA Grand Challenge contests many groups around the world have continued to actively research and work toward an autonomous vehicle capable of accomplishing a mission in a given context (e.g. desert, city) while following a set of prescribed rules, but none has been completely successful in uncontrolled environments, a task that many(More)
We present a framework for parameter and state estimation of personalized human kinematic models from motion capture data. These models can be used to optimize a variety of human-robot collaboration scenarios for the comfort or ergonomics of an individual human collaborator. Our approach offers two main advantages over prior approaches from the literature(More)
Several formulations based on Random Fields (RFs) have been proposed for joint categorization and segmentation (JCaS) of objects in images. The RF's sites correspond to pixels or superpixels of an image and one defines potential functions (typically over local neighborhoods) which define costs for the different possible assignments of labels to several(More)
Automatic recognition of human actions in video has been a highly addressed problem in robotics and computer vision. Majority of the recent work in literature has focused on classifying pre-segmented video clips, and some progress has also been made on joint detection and recognition of actions in complex video sequences. These methods, however, are not(More)
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