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Eli Shechtman

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Publications by Eli Shechtman (bibliography)

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2012
 
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Yang, Fei, Shechtman, Eli, Wang, Jue, Bourdev, Lubomir and Metaxas, Dimitris (2012): Face morphing using 3D-aware appearance optimization. In: Proceedings of the 2012 Conference on Graphics Interface 2012. pp. 93-99.

Traditional automatic face morphing techniques tend to generate blurry intermediate frames when the two input faces differ significantly. We propose a new face morphing approach that deals explicitly with large pose and expression variations. We recover the 3D face geometry of the input images using a projection on a pre-learned 3D face subspace. The geometry is interpolated by factoring the expression and pose and varying them smoothly across the sequence. Finally we pose the morphing problem as an iterative optimization with an objective that combines similarity of each frame to the geometry-induced warped sources, with a similarity between neighboring frames for temporal coherence. Experimental results show that our method can generate higher quality face morphing results for more extreme pose, expression and appearance changes than previous methods.

© All rights reserved Yang et al. and/or their publisher

2010
 
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Jacobs, David E., Goldman, Dan B. and Shechtman, Eli (2010): Cosaliency: where people look when comparing images. In: Proceedings of the 2010 ACM Symposium on User Interface Software and Technology 2010. pp. 219-228.

Image triage is a common task in digital photography. Determining which photos are worth processing for sharing with friends and family and which should be deleted to make room for new ones can be a challenge, especially on a device with a small screen like a mobile phone or camera. In this work we explore the importance of local structure changes?e.g. human pose, appearance changes, object orientation, etc.?to the photographic triage task. We perform a user study in which subjects are asked to mark regions of image pairs most useful in making triage decisions. From this data, we train a model for image saliency in the context of other images that we call cosaliency. This allows us to create collection-aware crops that can augment the information provided by existing thumbnailing techniques for the image triage task.

© All rights reserved Jacobs et al. and/or their publisher

 
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