Observing Human-Object Interactions: Using Spatial and Functional Compatibility for Recognition

TitleObserving Human-Object Interactions: Using Spatial and Functional Compatibility for Recognition
Publication TypeJournal Articles
Year of Publication2009
AuthorsGupta A, Kembhavi A, Davis LS
JournalPattern Analysis and Machine Intelligence, IEEE Transactions on
Pagination1775 - 1789
Date Published2009/10//
ISBN Number0162-8828
KeywordsAutomated;Recognition (Psychology);Video Recording;, Bayesian approach;functional compatibility;human perception;human-object interactions;objects recognition;psychological studies;spatial compatibility;Bayes methods;behavioural sciences;human factors;image recognition;motion estimation;object recognition;A, Biological;Movement;Pattern Recognition, Computer-Assisted;Models

Interpretation of images and videos containing humans interacting with different objects is a daunting task. It involves understanding scene or event, analyzing human movements, recognizing manipulable objects, and observing the effect of the human movement on those objects. While each of these perceptual tasks can be conducted independently, recognition rate improves when interactions between them are considered. Motivated by psychological studies of human perception, we present a Bayesian approach which integrates various perceptual tasks involved in understanding human-object interactions. Previous approaches to object and action recognition rely on static shape or appearance feature matching and motion analysis, respectively. Our approach goes beyond these traditional approaches and applies spatial and functional constraints on each of the perceptual elements for coherent semantic interpretation. Such constraints allow us to recognize objects and actions when the appearances are not discriminative enough. We also demonstrate the use of such constraints in recognition of actions from static images without using any motion information.