Representing and recognizing objects with massive local image patches

DOI10.1016/j.patcog.2011.06.011zbMath1225.68232OpenAlexW1984797383MaRDI QIDQ645863

Liang Lin, Kun Zeng, Ping Luo, Xiaowu Chen

Publication date: 10 November 2011

Published in: Pattern Recognition (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.patcog.2011.06.011

zbMATH Keywords

object recognitionobject detectiongenerative learning

Mathematics Subject Classification ID

Computing methodologies for image processing (68U10) Pattern recognition, speech recognition (68T10)

Related Items

Hierarchical mixing linear support vector machines for nonlinear classification

Uses Software

• AdaBoost.MH
• SIFT
• I2T

Cites Work

• A stochastic graph grammar for compositional object representation and recognition
• A decision-theoretic generalization of on-line learning and an application to boosting
• Additive logistic regression: a statistical view of boosting. (With discussion and a rejoinder by the authors)
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