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Computer Vision Group
TUM Department of Informatics
Technical University of Munich

Technical University of Munich

Home Research Areas Optical Flow Estimation


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research:optical_flow_estimation [2012/01/20 11:58] external edit
research:optical_flow_estimation [2015/09/24 21:16]
Caner Hazirbas
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 ====== Optical Flow Estimation ====== ====== Optical Flow Estimation ======
-Contact: [[members:​steinbrf|Frank Steinbrücker]]+ 
 +Estimating the motion of every pixel in a sequence of images is a problem with many applications in computer vision, such as image segmentation,​ object classification,​visual odometry, and driver assistance. 
 +In general, optical flow describes a sparse or dense vector field, where a displacement vector is assigned to certain pixel position, that points to where that pixel can be found in another image. 
 +In the context of scene flow estimation, which is performed on images with additional depth values, every pixel is assigned a depth displacement as well. 
 +Since much of the structural information of a 3D scene gets lost in the imaging process, so does the motion information. The estimation of the "​correct"​ projected motion in an image sequence is therefore highly ill-posed and has to be aided by additional priors such as the regularity of the motion. 
 +Our group mainly focuses on optical flow estimation by means of variational methods, that allow a clear formulation of the assumptions incorporated into the estimation process and generally produce dense vector fields. 
 +Contact: ​[[members:​hazirbas|Caner Hazırbaş]],​ [[members:​haeusser|Philip Häusser]], ​[[members:​steinbrf|Frank Steinbrücker]]
 ====== Related publications ====== ====== Related publications ======

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