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Time-correlated single photon counting and burst illumination laser data can be used for range profiling and target classification. In general, the problem is to analyze the response from a histogram of either photon counts or integrated intensities to assess the number, positions, and amplitudes of the reflected returns from object surfaces. The goal of(More)
We introduce the Hierarchical Partitioned Particle Filter (HPPF) designed specifically for articulated human tracking. The HPPF is motivated by the hierarchical dependency between the human body parameters and the partial independence between certain of those parameters. The tracking is model based and follows the analysis by synthesis principle. The(More)
We describe a novel architecture for automotive vision organized on five levels of abstraction, i.e., sensor, data, semantic, reasoning, and resource allocation levels, respectively. Although we implement and evaluate processes to detect and classify other participants within the immediate environment of a moving vehicle, our main emphasis is on the(More)
Theories of object recognition that are based purely on part decomposition do not take into account the role of textural, shading, and color information, nor do they differentiate between stylistic factors in the preparation of line-drawn pictorial stimuli. To investigate these factors, naming and verification experiments were performed using line drawings,(More)
We describe a scanning time-of-flight system which uses the time-correlated single-photon counting technique to produce three-dimensional depth images of distant, noncooperative surfaces when these targets are illuminated by a kHz to MHz repetition rate pulsed laser source. The data for the scene are acquired using a scanning optical system and an(More)
Developing parallel algorithms for intermediate and high levels of computer vision systems is addressed. Because the algorithms are complex and the nature and size of the input and output data sets vary for each application, the authors have directly developed parallel algorithms for dynamic control of both processing and communication complexity during(More)
This paper addresses the problem of generic object classification from three-dimensional depth or meshed data. First, surface patches are segmented on the basis of differential geometry and quadratic surface fitting. These are represented by a modified Gaussian image that includes the well-known shape index. Learning is an interactive process in which a(More)