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Fourth IEEE International Conference on Computer Vision Systems (ICVS'06)
Multi-camera Video Resolution Enhancement by Fusion of Spatial Disparity and Temporal Motion fields
New York, New York
January 04-January 07
ISBN: 0-7695-2506-7
Daniel Hazen, University of California, Berkeley
Rohit Puri, University of California, Berkeley
Kannan Ramchandran, University of California, Berkeley

In this work, we consider the problem of spatio-temporal resolution enhancement of a dynamic video scene by synergistically combining information from multiple video sequences corresponding to the different views of the scene. While prior work has focused on spatio-temporal superresolution by primarily exploiting the blurring correlation induced by the scene imaging process, in this work we exploit another and perhaps a stronger form of correlation the intrinsic correlation present in the dynamic scene. We use the knowledge base from the areas of multi-view computer vision, video coding and signal/image processing to efficiently model the dynamic video scene by exploiting inter-camera (space) as well as intra-camera correlations (time).

We present simulation results corresponding to a lowframe rate two-camera stereo video configuration where the sequences are combined to generate higher frame-rate sequences. Our proposed framework has direct application to problems such as multi-view video surveillance and relates closely to problems such as multi-view video compression.

Citation:
Daniel Hazen, Rohit Puri, Kannan Ramchandran, "Multi-camera Video Resolution Enhancement by Fusion of Spatial Disparity and Temporal Motion fields," icvs, pp.38, Fourth IEEE International Conference on Computer Vision Systems (ICVS'06), 2006
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