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Laser based environment recognition technologies have been developed recently. Especially moving objects detection and classification by laser scanners mounted on a mobility is required for mobile robots and autonomous cars. In this paper, we propose a moving objects detection and classification method based on grid trajectories acquired from sequential laser scan data. Grid trajectories are obtained...
Vision based human articulated body pose tracking has been historically important. Because analyzing multiple human activities, especially interaction between human in cluttered scenes is essential in visual surveillance scenarios, multiple people tracking has enjoyed much attention in human robot interaction research in recent years. In this paper, we newly introduce a robust framework for multiple...
This paper introduces a new foreground segmentation method. In contrast to most of the related works, our method uses only two image frames, a target frame to process, and a single reference frame. Our method first conducts simple thresholding like background subtraction, but then applies an iteration scheme we propose to estimate the pixel-wise likelihood of belonging to the foreground/background...
In this paper, we propose a robust recognition and segmentation method for daily actions with a novel multi-task sequence labeling algorithm called multi-task conditional random field (MT-CRF). Multi-Task sequence labeling is a task of assigning input sequence to sequence of multi-labels that consist of one or multiple symbols in single frame. Multi-Task sequence labeling is essential for action recognition,...
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