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— One of the most important tasks for mobile robots is to sense their environment. Further tasks might include the recognition of objects in the surrounding environment. Three dimensional range finders have become the sensors of choice for mapping the environment of a robot. Recognizing objects in point clouds provided by such sensors is a difficult task.(More)
With the proliferation of security cameras, the approach taken to monitoring and placement of these cameras is critical. This paper presents original work in the area of multiple camera human activity monitoring. First, a system is presented that tracks pedestrians across a scene of interest and recognizes a set of human activities. Next, a framework is(More)
— Cameras are becoming a common tool for automated vision purposes due to their low cost. Many surveillance and inspection systems include cameras as their sensor of choice. How useful these camera systems are is very dependent upon the positioning of the cameras. This is especially true if the cameras are to be used in automated systems as a beneficial(More)
— In this paper, we introduce a new covariance based feature descriptor to be used on " colored " point clouds gathered by a mobile robot equipped with an RGB-D camera. Although many recent descriptors provide adequate results, there is not yet a clear consensus on how to best tackle " colored " point clouds. We present the notion of a covariance on RGB-D(More)
— Object segmentation and classification is an important and difficult task in robotic vision. The task is complicated even further when the different objects are partially or completely occluded. Allowing a robot to take measurements from varying points of view can help in alleviating or completely removing occlusions. A robot equipped with an RGB-D sensor(More)