1 / 1

Online Selection of Discriminative Tracking Features

B. R+G+B. 2R+2G-B. Online Selection of Discriminative Tracking Features. By R. Collins and Y. Liu in ICCV 2003 Presenter: Roozbeh Mottaghi. Ranked based on a variance ratio. We would like log likelihood values of obj and bg: to be widely separated (high variance) AND

zenia-morse
Download Presentation

Online Selection of Discriminative Tracking Features

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. B R+G+B 2R+2G-B Online Selection of Discriminative Tracking Features By R. Collins and Y. Liu in ICCV 2003 Presenter: Roozbeh Mottaghi • Ranked based on a variance ratio. We would like log likelihood values of obj and bg: • to be widely separated (high variance) AND • tightly clustered in its own class (low variance) • The general idea is to adapt tracking feature set according to the current appearance of object and the background. • We are looking for most discriminative features. source: the paper

More Related