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Ping TAN |
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Associate Professor | ||||
School of Computing Science | ||||
Simon Fraser University | ||||
Email: |
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Structure-from-Motion & Visual SLAM | |
We are working to improve the efficiency and accuracy of the structure-from-motion algorithm, and to apply it for simultaneous localization and mapping (SLAM) applications. | |
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Structure-from-Motion (SFM) |
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Visual SLAM |
Computational Videography | |
Mobile devices make video capturing easy. We develop algorithms to enhance consumer videos by reducing the shake, stabilizing white balance changes, defogging, and generating artistic shots. |
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Video Stabilization |
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TrackCam |
Image-based Modeling | |
Realistic 3D models are important for computer graphics applications. Most existing modeling systems still heavily rely on user interactions to manually model details. We are working towards the goal of automatic creation of realistic 3D models from images of real objects. | |
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Image-based Tree Modeling Trees are everywhere and are difficult to model in a realistic way. We developed methods to easily recover realistic 3D models from 2D images. This approach was applied to small plants (SIGGRAPH 2006) and trees (SIGGRAPH 2007). We also developed a method for the extreme case when only one input image is available (SIGGRAPH Asia 2008). Video demos and 3D models can be found at the project page. |
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Image-based Architecture Modeling There is a strong demand for the photo-realistic modeling of cities for games, movies and map services. We applied the image-based modeling approach with street-level images to model buildings at the scale of a city block (SIGGRAPH Asia 2008) or a single building (SIGGRAPH Asia 2009). Video demos and 3D models can be found at the project page. |
Data-driven Media Synthesis | |
While professional artists can quickly create high-quality images and animations, most of the ordinary people cannot do that. We are exploiting the large amount of visual data to design algorithms in a data-driven approach to simplify media creation. | |
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Sketch2Photo
A picture is worth a thousand words, and not surprisingly, people often use pictures and animations to convey ideas and stories. We developed methods to automatically convert an annotated freehand doodle into a realistic picture (SIGGRAPH Asia 2009) or a comic strip (TVCG 2012). More details can be found in the paper and the project page. The image search and filtering technique behind this application is extended in the 'semantic colorization' (SIGGRAPH Asia 2011) to allow users quickly to turn a grayscale image into color. |
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Virtual Clothes Try-on |
Reflectance Analysis | |
An image of an object is determined through complex interactions between its shape, material, illumination, and the imaging process. We are seeking to invert this process and recover scene information. | |
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Photometric Stereo
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Reflectance Separation Intrinsic images: An image might be separated into two intrinsic components: texture and shading. We introduce a non-local constraint to relate texture values at far apart pixels (CVPR2008). Closed-form solution can be derived from this constraint (PAMI2012). Depth sensor can also be used to further improve this separation (ECCV2012). Highlight removal: Surface reflectance can also be separated into diffuse and specular components, each with different physical properties. We developed methods to achieve this separation of regular surfaces (ICCV2003) and texture surfaces (CVPR2006). |
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Last modified in Jul 2015 |