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The paper proposes a novel endoscope motion estimation method that bases an aggressive particle filter (APF) for enhancing electromagnetic tracking (EMT) during guided endoscopy. We explore an APF strategy to resolve two main limitations of EMT sensor measurements: (1) inaccuracy due to airway deformation and (2) instability or jitter errors because of magnetic field distortion. During such a strategy,...
Eye detector and eye tracker have been individually used to solve the task of eye localization in video. Although the eye detection based approach seems to be robust especially in frontal view faces and opened eyes, its performance drops dramatically in the presence of large head pose change and closed eyes. Meanwhile, eye tracking based approaches can estimate closed eyes and eyes in extreme head...
It is suggested how a Markov random field can be used for object tracking with context information. The tracking is formulated as a two layer process. In the first phase, the image is represented by a set of feature points which are tracked by a standard tracker. In the second phase, the proposed semi-supervised learning and labeling algorithm is used to label the points to three classes — object,...
This paper presents a novel method for pedestrian counting in surveillance videos, which localizes and tracks the head-shoulders of pedestrians via the integrated bottom-up/top-down processes. In the bottom-up stage, we extract and match informative local image features crossing frames to obtain the initial moving regions (i.e. potential pedestrians). The top-down stage comprises two steps: (i) head-shoulder...
In this paper, we propose a new method to track players using 3D particle filter guided by the time-situation graph in order to perform players tracking robust to occlusion in a soccer image sequence. In the conventional method using particle filter, there is a deficit that it is difficult to discover the players again once they are lost in an image sequence. Thus, we represents the position information...
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