Skip to Main content Skip to Navigation
Conference papers

Combining Appearance Models and Markov Random Fields for Category Level Object Segmentation

Diane Larlus 1 Frédéric Jurie 2
1 LEAR - Learning and recognition in vision
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology
2 Equipe Image - Laboratoire GREYC - UMR6072
GREYC - Groupe de Recherche en Informatique, Image et Instrumentation de Caen
Abstract : Object models based on bag-of-words representations can achieve state-of-the-art performance for image classification and object localization tasks. However, as they consider objects as loose collections of local patches they fail to accurately locate object boundaries and are not able to produce accurate object segmentation. On the other hand, Markov random field models used for image segmentation focus on object boundaries but can hardly use the global constraints necessary to deal with object categories whose appearance may vary significantly. In this paper we combine the advantages of both approaches. First, a mechanism based on local regions allows object detection using visual word occurrences and produces a rough image segmentation. Then, a MRF component gives clean boundaries and enforces label consistency, guided by local image cues (color, texture and edge cues) and by long-distance dependencies. Gibbs sampling is used to infer the model. The proposed method successfully segments object categories with highly varying appearances in the presence of cluttered backgrounds and large view point changes. We show that it outperforms published results on the Pascal VOC 2007 dataset.
Document type :
Conference papers
Complete list of metadata

Cited literature [19 references]  Display  Hide  Download
Contributor : Thoth Team Connect in order to contact the contributor
Submitted on : Monday, December 20, 2010 - 10:24:53 AM
Last modification on : Thursday, January 20, 2022 - 5:31:01 PM
Long-term archiving on: : Monday, November 5, 2012 - 2:40:22 PM


Files produced by the author(s)



Diane Larlus, Frédéric Jurie. Combining Appearance Models and Markov Random Fields for Category Level Object Segmentation. CVPR 2008 - IEEE Conference on Computer Vision & Pattern Recognition, Jun 2008, Anchorage, United States. pp.1-7, ⟨10.1109/CVPR.2008.4587453⟩. ⟨inria-00548660⟩



Les métriques sont temporairement indisponibles