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dc.contributor.authorRachavarapu, Kranthi Kumaren_US
dc.contributor.authorKumar, Moneishen_US
dc.contributor.authorGandhi, Vineeten_US
dc.contributor.authorSubramanian, Ramanathanen_US
dc.contributor.editorGutierrez, Diego and Sheffer, Allaen_US
dc.date.accessioned2018-04-14T18:24:02Z
dc.date.available2018-04-14T18:24:02Z
dc.date.issued2018
dc.identifier.issn1467-8659
dc.identifier.urihttp://dx.doi.org/10.1111/cgf.13354
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf13354
dc.description.abstractWe present a novel approach to optimally retarget videos for varied displays with di ering aspect ratios by preserving salient scene content discovered via eye tracking. Our algorithm performs editing with cut, pan and zoom operations by optimizing the path of a cropping window within the original video while seeking to (i) preserve salient regions, and (ii) adhere to the principles of cinematography. Our approach is (a) content agnostic as the same methodology is employed to re-edit a wide-angle video recording or a close-up movie sequence captured with a static or moving camera, and (b) independent of video length and can in principle re-edit an entire movie in one shot. Our algorithm consists of two steps. The first step employs gaze transition cues to detect time stamps where new cuts are to be introduced in the original video via dynamic programming. A subsequent step optimizes the cropping window path (to create pan and zoom e ects), while accounting for the original and new cuts. The cropping window path is designed to include maximum gaze information, and is composed of piecewise constant, linear and parabolic segments. It is obtained via L(1) regularized convex optimization which ensures a smooth viewing experience. We test our approach on a wide variety of videos and demonstrate significant improvement over the state-of-the-art, both in terms of computational complexity and qualitative aspects. A study performed with 16 users confirms that our approach results in a superior viewing experience as compared to gaze driven re-editing [JSSH15] and letterboxing methods, especially for wide-angle static camera recordings.en_US
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectCCS Concepts Computing methodologies
dc.subjectScene Understanding
dc.subjectImage
dc.subjectbased rendering
dc.subject Theory of computation
dc.subjectDynamic programming
dc.subjectConvex optimization
dc.titleWatch to Edit: Video Retargeting using Gazeen_US
dc.description.seriesinformationComputer Graphics Forum
dc.description.sectionheadersGaze and Attention
dc.description.volume37
dc.description.number2
dc.identifier.doi10.1111/cgf.13354
dc.identifier.pages205-215


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