Hand-shadow illusions and 3D DDR based on efficient model retrieval
ACM SIGGRAPH 2006 Emerging technologies
Parametric reshaping of human bodies in images
ACM SIGGRAPH 2010 papers
Data-driven suggestions for creativity support in 3D modeling
ACM SIGGRAPH Asia 2010 papers
Proceedings of the international conference on Multimedia
ShadowDraw: real-time user guidance for freehand drawing
ACM SIGGRAPH 2011 papers
Video retrieval by mimicking poses
Proceedings of the 2nd ACM International Conference on Multimedia Retrieval
Crowdsourced Learning to Photograph via Mobile Devices
ICME '12 Proceedings of the 2012 IEEE International Conference on Multimedia and Expo
Retrieval and Visualization of Human Motion Data via Stick Figures
Computer Graphics Forum
KinEmotion: context controllable emotional motion analysis method for interactive cartoon generator
ACM SIGGRAPH 2013 Posters
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Next to lighting, posing is the most challenging aspect of portrait photography. A commonly adopted solution is to learn by example, which is beneficial for both trained photographers and novice users, especially when subjects have no clue about how to pose themselves. A collection of portrait images by professionals (e.g., [Perkins 2009]) provides a resource for photographers seeking inspiration for their own work. Such handful posing references (e.g., Posing App) have also been made available to smartphone platforms, which offer the unique possibility of directly overlaying camera view with a reference pose as visual guidance.