Probabilistic Graph Based Object Category Recognition Using the Context of Object-Action Interaction 


Vol. 40,  No. 11, pp. 2284-2290, Nov.  2015


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  Abstract

The use of human actions as context for object class recognition is quite effective in enhancing the recognition performance despite the large variation in the appearance of objects. We propose an efficient method that integrates human action information into object class recognition using a Bayesian appraoch based on a simple probabilistic graph model. The experiment shows that by using human actions ac context information we can improve the performance of the object calss recognition from 8% to 28%.

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  Cite this article

[IEEE Style]

S. Yoon, S. Bae, H. Park, J. Yi, "Probabilistic Graph Based Object Category Recognition Using the Context of Object-Action Interaction," The Journal of Korean Institute of Communications and Information Sciences, vol. 40, no. 11, pp. 2284-2290, 2015. DOI: .

[ACM Style]

Sung-baek Yoon, Se-ho Bae, Han-je Park, and June-ho Yi. 2015. Probabilistic Graph Based Object Category Recognition Using the Context of Object-Action Interaction. The Journal of Korean Institute of Communications and Information Sciences, 40, 11, (2015), 2284-2290. DOI: .

[KICS Style]

Sung-baek Yoon, Se-ho Bae, Han-je Park, June-ho Yi, "Probabilistic Graph Based Object Category Recognition Using the Context of Object-Action Interaction," The Journal of Korean Institute of Communications and Information Sciences, vol. 40, no. 11, pp. 2284-2290, 11. 2015.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880