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Algorithms for video retargeting

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Abstract

The visualization of high resolution video on small mobile devices is still a great challenge today. Most critical are the limited display resolution and different aspect ratios of handheld mobile devices. So far, there is no retargeting algorithm available that guarantees good results for all videos. We introduce a new video retargeting approach that reduces the resolution while preserving as much of the relevant content as possible. A central component of the system selects the most suitable algorithm to adapt a given shot. We have implemented two retargeting algorithms: a region of interest (ROI) based technique, and a fast implementation of seam carving for size adaptation of videos (FSCAV). The ROI-based retargeting detects important regions like faces, objects, text, and contrast-based saliency regions. A rectangular window within the larger frame is selected that defines the visible area of the target video. If several relevant regions are detected, an artificial camera motion (pan, tilt, or zoom) may change the selected view within a shot. For seam carving, we present two extensions: The first reduces the distortion of straight lines (lines may become curved or disconnected); the second avoids jitter in the target video, limits the large memory requirements and computational effort of seam carving, and makes it applicable to video retargeting. In addition, we present a heuristic that estimates the visual quality of the target video. If the quality drops below a threshold, the ROI-based retargeting is used for this shot. User evaluations confirm a very high visual quality of our approach.

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Acknowledgements

The authors acknowledge the financial support granted by the Deutsche Forschungsgemeinschaft (DFG). We would like to thank the following flickr.com users for providing their images via the creative commons license: teoruiz (bridge.jpg), the_tahoe_guy (road.jpg) and digital_cat (construction_site.jpg). We thank Instituto Luce for providing historical films within the European research project ECHO. Furthermore, we would like to thank Sabine Olawsky for the development of the contrast-based saliency detection.

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  1. Department of Computer Science IV, University of Mannheim, Mannheim, Germany

    Stephan Kopf, Thomas Haenselmann, Johannes Kiess, Benjamin Guthier & Wolfgang Effelsberg

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Kopf, S., Haenselmann, T., Kiess, J. et al. Algorithms for video retargeting. Multimed Tools Appl 51, 819–861 (2011). https://doi.org/10.1007/s11042-010-0717-6

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