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

Project/Team LEAR : Learning and Recognition in Vision

Cordelia Schmid 1, * 
* Corresponding author
1 LEAR - Learning and recognition in vision
GRAVIR - IMAG - Laboratoire d'informatique GRAphique, VIsion et Robotique de Grenoble, Inria Grenoble - Rhône-Alpes, CNRS - Centre National de la Recherche Scientifique : FR71
Abstract : LEAR's main focus is learning based approaches to visual object recognition and scene interpretation, particularly for image retrieval, video indexing and the analysis of humans and their movements. Understanding the content of everyday images and videos is one of the fundamental challenges of computer vision and we believe that significant advances will be made over the next few years by combining state of the art image analysis tools with emerging machine learning and statistical modeling techniques.
Keywords : LEAR
Complete list of metadata

Cited literature [80 references]  Display  Hide  Download
Contributor : THOTH Team Connect in order to contact the contributor
Submitted on : Monday, December 20, 2010 - 9:49:04 AM
Last modification on : Wednesday, February 2, 2022 - 3:58:13 PM
Long-term archiving on: : Monday, March 21, 2011 - 3:17:38 AM


Files produced by the author(s)


  • HAL Id : inria-00548572, version 1



Cordelia Schmid. Project/Team LEAR : Learning and Recognition in Vision. [Technical Report] 2006, pp.36. ⟨inria-00548572⟩



Record views


Files downloads