Recognizing and Learning
Awarded the Best Short Course Prize at ICCV 2005
Li Fei-Fei (Stanford), Rob Fergus (NYU), Antonio Torralba (MIT)
This course reviews current methods for object category recognition,
dividing them into four main areas: bag of words models; parts
and structure models; discriminative methods and combined recognition and
segmentation. The emphasis will be on the important general concepts
rather than in depth coverage of contemporary papers. The course is accompanied by extensive Matlab demos.
ICCV 2009 Recognizing and Learning Object Categories: Year 2009
Slides CVPR 2007
Slides ICCV 2005
| This set of three demos illustrates the concepts behind
several approaches for object recognition. The code consists of Matlab
scripts (which should run under both Windows and Linux). The code is for
teaching/research purposes only.
|Bag of words models||A simple parts and structure model||A simple detector with boosting|
This work was partially supported by the National Science Foundation Grant No. 0413232. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.