Skip to content

Research at St Andrews

An efficient Naive Bayes approach to category-level object detection

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


Kasim Terzic, J. M.H. Du Buf

School/Research organisations


We present a fast Bayesian algorithm for category-level object detection in natural images. We modify the popular Naive Bayes Nearest Neighbour classification algorithm to make it suitable for evaluating multiple sub-regions in an image, and offer a fast, filtering-based alternative to the multi-scale sliding window approach. Our algorithm is example-based and requires no learning. Tests on standard datasets and robotic scenarios show competitive detection rates and real-time performance of our algorithm.



Original languageEnglish
Title of host publication2014 IEEE International Conference on Image Processing, ICIP 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages5
ISBN (Electronic)9781479957514
Publication statusPublished - 28 Jan 2014

    Research areas

  • Computer vision, Nearest neighbour, Object detection, Real time systems, Robot vision

Discover related content
Find related publications, people, projects and more using interactive charts.

View graph of relations

Related by author

  1. Supervisor recommendation tool for Computer Science projects

    Zemaityte, G. & Terzic, K., 9 Jan 2019, Proceedings of the 3rd Conference on Computing Education Practice (CEP '19) . New York: ACM, 4 p. 1

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

  2. BINK: Biological Binary Keypoint Descriptor

    Saleiro, M., Terzić, K., Rodrigues, J. M. F. & du Buf, J. M. H., Dec 2017, In : BioSystems. 162, p. 147-156

    Research output: Contribution to journalArticle

  3. Texture features for object salience

    Terzić, K., Krishna, S. & du Buf, J. M. H., Nov 2017, In : Image and Vision Computing. 67, p. 43-51

    Research output: Contribution to journalArticle

  4. Interpretable feature maps for robot attention

    Terzić, K. & du Buf, J. M. H., 2017, Universal Access in Human–Computer Interaction. Design and Development Approaches and Methods: 11th International Conference, UAHCI 2017, Held as Part of HCI International 2017, Vancouver, BC, Canada, July 9–14, 2017, Proceedings, Part I. Antona, M. & Stephanidis, C. (eds.). Cham: Springer, p. 456-467 12 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 10277).

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

  5. Methods for reducing visual discomfort in stereoscopic 3D: a review

    Terzić, K. & Hansard, M., Sep 2016, In : Signal Processing: Image Communication. 47, p. 402-416 15 p.

    Research output: Contribution to journalReview article

ID: 255500434