'Affordance' detection by mid-level physical parts

Mahmudul Hassan, Anuja Dharmaratne

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review


Derived from ecological psychology, the term 'affordance' refers to the functional classification of objects. It simply means the set of actions a subject (i.e. humans and anthropomorphic agents) can possibly perform with an object. There are several paradigms in the researches regarding the approaches of affordance detection. These approaches include considering other contexts like the subject, ambient environment, scene etc. along with the object to detect the affordance. But the core challenge, which is to identify the affordance of an object with mere its visual features is still open ended. The orthodox approaches often used the fine level image features (i.e. HOG, SIFT) and perform bottom up processing to detect affordance. In this paper, we propose an effective methodology of using 'mid-level physical parts' of objects as features for affordance detection. It is a multi-layered detection problem, where the simple image features are used to detect mid-level physical parts of an object and subsequently those parts are used to detect affordance. Our experiment results show the effectiveness of our method over the current affordance detection techniques. Moreover since the parts may be shared between different object classes, the method is also proficient in generality.

Original languageEnglish
Title of host publication2015 International Conference on Image and Vision Computing New Zealand, IVCNZ 2015
PublisherIEEE, Institute of Electrical and Electronics Engineers
ISBN (Electronic)9781509003570
Publication statusPublished - 2015
EventImage and Vision Computing New Zealand (IVCNZ) 2015 - Auckland, New Zealand
Duration: 23 Nov 201524 Nov 2015
Conference number: 30th
https://ieeexplore.ieee.org/xpl/conhome/7748304/proceeding (Proceedings)

Publication series

NameInternational Conference Image and Vision Computing New Zealand
ISSN (Print)2151-2191
ISSN (Electronic)2151-2205


ConferenceImage and Vision Computing New Zealand (IVCNZ) 2015
Abbreviated titleIVCNZ 2015
Country/TerritoryNew Zealand
Internet address


  • Affordance
  • Mid-level Physical Parts
  • Visual Features

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