Machine learning applications in computer vision

Mehrtash Harandi, Javid Taheri, Brian C. Lovell

Research output: Chapter in Book/Report/Conference proceedingChapter (Book)Researchpeer-review

1 Citation (Scopus)

Abstract

Recognizing objects based on their appearance (visual recognition) is one of the most significant abilities of many living creatures. In this study, recent advances in the area of automated object recognition are reviewed; the authors specifically look into several learning frameworks to discuss how they can be utilized in solving object recognition paradigms. This includes reinforcement learning, a biologicallyinspired machine learning technique to solve sequential decision problems and transductive learning, and a framework where the learner observes query data and potentially exploits its structure for classification. The authors also discuss local and global appearance models for object recognition, as well as how similarities between objects can be learnt and evaluated.

Original languageEnglish
Title of host publicationImage Processing
Subtitle of host publicationConcepts, Methodologies, Tools, and Applications
PublisherIGI Global
Pages896-926
Number of pages31
Volume2-3
ISBN (Electronic)9781466639959
ISBN (Print)1466639946, 9781466639942
DOIs
Publication statusPublished - 31 May 2013
Externally publishedYes

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