Object Recognition with Cluster Matching
Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
Within this thesis an algorithm for object recognition called Cluster Matching has been developed, implemented and evaluated. The image information is sampled at arbitrary sample points, instead of interest points, and local image features are extracted. These sample points are used as a compact representation of the image data and can quickly be searched for prior known objects. The algorithm is evaluated on a test set of images and the result is surprisingly reliable and time efficient.
Place, publisher, year, edition, pages
2009. , 62 p.
computer vision, object recognition, cluster matching
Computer Vision and Robotics (Autonomous Systems)
IdentifiersURN: urn:nbn:se:liu:diva-51494ISRN: LITH-ISY-EX--09/4152--SEOAI: oai:DiVA.org:liu-51494DiVA: diva2:284633
Subject / course
Computer Vision Laboratory
2009-10-06, Algoritmen, B-huset ingång 27, Linköping, 15:15 (Swedish)
Felsberg, Michael, Prof