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Rolling shutter image sensors are increasingly used over global shutter sensors due to their lower cost and reduced size. As is well known in the computer vision community, one drawback of rolling shutter sensors is that they introduce geometric distortions, such as skew or wobble, when either the sensor or objects in the scene move. This problem has received a great deal of attention, and robust...
We address the problem of motion blur removal using a computational camera with a fluttering shutter. While there are several prototype flutter shutter cameras, and many scenarios in which motion blur is problematic, there are few real-world uses of flutter shutter cameras due to two important limitations. The first is that the shutter mechanisms used to date - primarily Liquid Crystal Display (LCD)...
We address motion de-blurring using a computational camera that captures an image while the stabilizing optical element moves in a modified Canon IS lens. Our work builds on that of Levin et al. [11], who introduce parabolic motion as a means of achieving invariance to unknown subject velocity in an a priori known direction. While the previous work addresses a specific scenario - exact knowledge of...
Images with GPS coordinates are a rich source of information about a geographic location. Innovative user services and applications are being built using geotagged images taken from community contributed repositories like Flickr. Only a small subset of the images in these repositories is geotagged, limiting their exploration and effective utilization. We propose to use optional meta-data along with...
We propose a method for human activity recognition in videos, based on shape analysis. We define local shape descriptors for interest points on the detected contour of the human action and build an action descriptor using a Bag of Features method. We also use the temporal relation among matching interest points across successive video frames. Further, an SVM is trained on these action descriptors...
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