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Analyzing Structural Characteristics of Object Category Representations From Their Semantic-part Distributions

Sarvadevabhatla, Ravi Kiran and Babu, Venkatesh R (2016) Analyzing Structural Characteristics of Object Category Representations From Their Semantic-part Distributions. In: 24th ACM Multimedia Conference (MM), OCT 15-19, 2016, Amsterdam, NETHERLANDS, pp. 92-96.

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Official URL: http://dx.doi.org/10.1145/2964284.2967190


Studies from neuroscience show that part-mapping computations are employed by human visual system in the process of object recognition. In this paper, we present an approach for analyzing semantic-part characteristics of object category representations. For our experiments, we use category epitome, a recently proposed sketch-based spatial representation for objects. To enable part-importance analysis, we first obtain semantic-part annotations of hand-drawn sketches originally used to construct the epitomes. We then examine the extent to which the semantic-parts are present in the epitomes of a category and visualize the relative importance of parts as a word cloud. Finally, we show how such word cloud visualizations provide an intuitive understanding of category-level structural trends that exist in the category epitome object representations. Our method is general in applicability and can also be used to analyze part-based visual object representations for other depiction methods such as photographic images.

Item Type: Conference Proceedings
Additional Information: Copy right for this article belongs to the ASSOC COMPUTING MACHINERY, 1515 BROADWAY, NEW YORK, NY 10036-9998 USA
Department/Centre: Division of Interdisciplinary Sciences > Computational and Data Sciences
Date Deposited: 30 Dec 2016 07:20
Last Modified: 16 Oct 2018 10:45
URI: http://eprints.iisc.ac.in/id/eprint/55656

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