Please use this identifier to cite or link to this item:
https://doi.org/10.1109/ICIP.2007.4379288
DC Field | Value | |
---|---|---|
dc.title | Real-time pedestrian detection using eigenflow | |
dc.contributor.author | Goel D. | |
dc.contributor.author | Chen T. | |
dc.date.accessioned | 2018-08-21T05:08:22Z | |
dc.date.available | 2018-08-21T05:08:22Z | |
dc.date.issued | 2006 | |
dc.identifier.citation | Goel D., Chen T. (2006). Real-time pedestrian detection using eigenflow. Proceedings - International Conference on Image Processing, ICIP 3 : III229-III232. ScholarBank@NUS Repository. https://doi.org/10.1109/ICIP.2007.4379288 | |
dc.identifier.isbn | 1424414377 | |
dc.identifier.isbn | 9781424414376 | |
dc.identifier.issn | 15224880 | |
dc.identifier.uri | http://scholarbank.nus.edu.sg/handle/10635/146286 | |
dc.description.abstract | We propose a novel learning algorithm to detect moving pedestrians from a stationary camera in real-time. The algorithm learns a discriminative model based on eigenflow, i.e., the eigenvectors derived from applying Principal Component Analysis to the optical flow of moving objects, to differentiate between human motion patterns from other kind of motions like of cars etc. The learned model is a cascade of Adaboost classifiers of increasing complexity, with eigenflow vectors as the weak classifiers. Unlike some recent attempts to use motion for pedestrian detection, this system works in real-time. Moreover, the system is robust to small camera motion and slow illumination changes, and can detect moving children even though the training data had only adult pedestrians. | |
dc.source | Scopus | |
dc.subject | AdaBoost | |
dc.subject | Optical flow | |
dc.subject | PCA | |
dc.type | Conference Paper | |
dc.contributor.department | OFFICE OF THE PROVOST | |
dc.contributor.department | DEPARTMENT OF COMPUTER SCIENCE | |
dc.description.doi | 10.1109/ICIP.2007.4379288 | |
dc.description.sourcetitle | Proceedings - International Conference on Image Processing, ICIP | |
dc.description.volume | 3 | |
dc.description.page | III229-III232 | |
dc.published.state | published | |
Appears in Collections: | Staff Publications |
Show simple item record
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.