Service interruption on Monday 11 July from 12:30 to 13:00: all the sites of the CCSD (HAL, Epiciences, SciencesConf, AureHAL) will be inaccessible (network hardware connection).
Skip to Main content Skip to Navigation
Conference papers

MULTIPLE OBJECT TRACKING WITH OCCLUSIONS USING HOG DESCRIPTORS AND MULTI RESOLUTION IMAGES

Abstract : We present an algorithm for tracking multiple objects through occlusions. Firstly, for each detected object we compute feature points using the FAST algorithm [1]. Secondly, for each feature point we build a descriptor based on the Histogram of Oriented Gradients (HOG) [2]. Thirdly, we track feature points using these descriptors. Object tracking is possible even if objects are occluded. If few objects are merged and detected as a single one, we assign each newly detected feature point in such single object to one of these occluded objects. We apply probabilistic methods for this task, using information from the previous frames like object size and motion (speed and orientation). We use multi resolution images to decrease the processing time. Our approach is tested on the synthetic video sequence, the KTH dataset [3] and the CAVIAR dataset [4]. All tests confirm the effectiveness of our approach.
Document type :
Conference papers
Complete list of metadata

Cited literature [13 references]  Display  Hide  Download

https://hal.inria.fr/inria-00510410
Contributor : Piotr Bilinski Connect in order to contact the contributor
Submitted on : Monday, September 6, 2010 - 10:19:45 AM
Last modification on : Friday, February 4, 2022 - 3:24:46 AM
Long-term archiving on: : Tuesday, December 7, 2010 - 2:34:58 AM

File

ICDP09.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : inria-00510410, version 2

Collections

Citation

Piotr Bilinski, François Bremond, Mohamed Kaâniche. MULTIPLE OBJECT TRACKING WITH OCCLUSIONS USING HOG DESCRIPTORS AND MULTI RESOLUTION IMAGES. 3rd International Conference on Imaging for Crime Detection and Prevention, Dec 2009, London, United Kingdom. ⟨inria-00510410v2⟩

Share

Metrics

Record views

216

Files downloads

417