PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

The Pascal Visual Object Classes (VOC) Challenge
Mark Everingham, Luc Van Gool, Christopher Williams, John Winn and Andrew Zisserman
International Journal of Computer Vision (IJCV) Volume 88, Number 2, pp. 303-338, 2010. ISSN 0920-5691 (Print) 1573-1405 (Online)

Abstract

The Pascal Visual Object Classes (VOC) challenge is a benchmark in visual object category recognition and detection, providing the vision and machine learning communities with a standard dataset of images and annotation, and standard evaluation procedures. Organised annually from 2005 to present, the challenge and its associated dataset has become accepted as the benchmark for object detection. This paper describes the dataset and evaluation procedure. We review the state-of-the-art in evaluated methods for both classification and detection, analyse whether the methods are statistically different, what they are learning from the images (e.g. the object or its context), and what the methods find easy or confuse. The paper concludes with lessons learnt in the three year history of the challenge, and proposes directions for future improvement and extension.

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EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Machine Vision
ID Code:6961
Deposited By:Karteek Alahari
Deposited On:25 June 2010