Debi Prosad Dogra

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In this paper, we present a method for autonomously detecting and extracting region(s)-of-interest (ROI) from surveillance videos using trajectory-based analysis. Our approach, localizes ROI in a stochastic manner using correlated probability density functions that model motion dynamics of multiple moving targets. The motion dynamics model is built by(More)
Most of the existing video object detection schemes are either computationally extensive or fail to detect moving objects in different challenging situations. In this paper, we propose a robust and computationally inexpensive scheme to detect moving objects in video. The threefold approach begins with computation of difference images using temporal(More)
In this paper, we propose a smart video summarization technique that compiles a synopsis of event(s)-of-interest occurring within a segment of image frames in a video. The proposed solution space consists of extracting appropriate features that represent the dynamics of targets in surveillance environments using their motion trajectories combined with a(More)
In this paper, we propose a method for detecting variations in the Pulse Rate (PR) of infants undergoing the Hammersmith Infant Neurological Examinations (HINE) using video data. As in every other medical examination the measurement of the PR is critical to underpin the physiological state of living beings. During HINE, measuring the infant's PR is(More)