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Nick@CVPR: Performance & Evalu…

Author:admin @ June 25th, 2009 Comments Off

Nick@CVPR: Performance & Evaluation of Tracking & Surveilance (PETS) Workshop began at Face & Gesture. Each year they publish a new dataset.

Nick@CVPR: Ta et al. used SURF…

Author:admin @ June 24th, 2009 Comments Off

Nick@CVPR: Ta et al. used SURF features similar to SIFT to track feature points & do recognition on Nokia cell phones.

Nick@CVPR: Piotr Dollar compar…

Author:admin @ June 24th, 2009 Comments Off

Nick@CVPR: Piotr Dollar compared 12 methods for pedestrian tracking. The fastest is about 0.1FPS so he recommends we try MIPOMDP there.

A reading robot from Waseda Un…

Author:admin @ June 24th, 2009 Comments Off

A reading robot from Waseda University. Note the design reminiscent of RUBI3. http://bit.ly/FD3bs

Nick@CVPR: Denzler’s studens c…

Author:admin @ June 24th, 2009 Comments Off

Nick@CVPR: Denzler’s studens check if two cameras are aligned by probabilities of point wise correspondence. Low entropy means aligned.

Nick@CVPR: Bruce at Inria uses…

Author:admin @ June 24th, 2009 Comments Off

Nick@CVPR: Bruce at Inria uses dist. of Harris detectors in Natural inputs to choose which corners to accept. A lot can still be done here.

Nick@CVPR: Bolme et al. from C…

Author:admin @ June 24th, 2009 Comments Off

Nick@CVPR: Bolme et al. from Colorado have a way to learn good filters for eye detection by learning many okay filters and averaging them.

Nick@CVPR: Both Fei-Fei Li and…

Author:admin @ June 24th, 2009 Comments Off

Nick@CVPR: Both Fei-Fei Li and Jitendra Malik get a lot out of over-segmenting images & then inferring which segments go with which object.

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