Reconstruction of articulated objects from point correspondences in a single uncalibrated image
Computer Vision and Image Understanding
Recovering 3D Human Pose from Monocular Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
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
Learning a 3D Human Pose Distance Metric from Geometric Pose Descriptor
IEEE Transactions on Visualization and Computer Graphics
Video retrieval by mimicking poses
Proceedings of the 2nd ACM International Conference on Multimedia Retrieval
A search-classify approach for cluttered indoor scene understanding
ACM Transactions on Graphics (TOG) - Proceedings of ACM SIGGRAPH Asia 2012
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
PoseShop: Human Image Database Construction and Personalized Content Synthesis
IEEE Transactions on Visualization and Computer Graphics
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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.