Detecting and Grouping Identical Objects for Region Proposal and Classification

Wim Abbeloos, Sergio Caccamo, Esra Ataer-Cansizoglu, Yuichi Taguchi, Chen Feng, Teng Yok Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Often multiple instances of an object occur in the same scene, for example in a warehouse. Unsupervised multi-instance object discovery algorithms are able to detect and identify such objects. We use such an algorithm to provide object proposals to a convolutional neural network (CNN) based classifier. This results in fewer regions to evaluate, compared to traditional region proposal algorithms. Additionally, it enables using the joint probability of multiple instances of an object, resulting in improved classification accuracy. The proposed technique can also split a single class into multiple sub-classes corresponding to the different object types, enabling hierarchical classification.

Original languageEnglish (US)
Title of host publicationProceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2017
PublisherIEEE Computer Society
Pages501-502
Number of pages2
ISBN (Electronic)9781538607336
DOIs
StatePublished - Aug 22 2017
Event30th IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2017 - Honolulu, United States
Duration: Jul 21 2017Jul 26 2017

Publication series

NameIEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
Volume2017-July
ISSN (Print)2160-7508
ISSN (Electronic)2160-7516

Other

Other30th IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2017
CountryUnited States
CityHonolulu
Period7/21/177/26/17

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

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  • Cite this

    Abbeloos, W., Caccamo, S., Ataer-Cansizoglu, E., Taguchi, Y., Feng, C., & Lee, T. Y. (2017). Detecting and Grouping Identical Objects for Region Proposal and Classification. In Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2017 (pp. 501-502). [8014810] (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops; Vol. 2017-July). IEEE Computer Society. https://doi.org/10.1109/CVPRW.2017.76