What, Where and How Many? Combining Object Detectors and CRFs View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2010

AUTHORS

Ľubor Ladický , Paul Sturgess , Karteek Alahari , Chris Russell , Philip H. S. Torr

ABSTRACT

Computer vision algorithms for individual tasks such as object recognition, detection and segmentation have shown impressive results in the recent past. The next challenge is to integrate all these algorithms and address the problem of scene understanding. This paper is a step towards this goal. We present a probabilistic framework for reasoning about regions, objects, and their attributes such as object class, location, and spatial extent. Our model is a Conditional Random Field defined on pixels, segments and objects. We define a global energy function for the model, which combines results from sliding window detectors, and low-level pixel-based unary and pairwise relations. One of our primary contributions is to show that this energy function can be solved efficiently. Experimental results show that our model achieves significant improvement over the baseline methods on CamVid and pascal voc datasets. More... »

PAGES

424-437

References to SciGraph publications

Book

TITLE

Computer Vision – ECCV 2010

ISBN

978-3-642-15560-4
978-3-642-15561-1

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-642-15561-1_31

DOI

http://dx.doi.org/10.1007/978-3-642-15561-1_31

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1018304069


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