Paper Info
Title
Eye of the Dragon: Exploring Discriminatively Minimalist Sketch-based Abstractions for Object Categories
Abstract
As a form of visual representation, freehand line sketches are typically studied as an end product of the sketching process. However, from a recognition point of view, one can also study various orderings and properties of the primitive strokes that compose the sketch. Studying sketches in this manner has enabled us to create novel sparse yet discriminative sketch-based representations for object categories which we term category-epitomes. Concurrently, the epitome construction provides a natural measure for quantifying the sparseness underlying the original sketch, which we term epitome-score. We analyze category-epitomes and epitome-scores for hand-drawn sketches from a sketch dataset of 160 object categories commonly encountered in daily life. Our analysis provides a novel viewpoint for examining the complexity of representation for visual object categories.
Year
DOI
Venue
2015
10.1145/2733373.2806230
ACM Multimedia
Keywords
Field
DocType
freehand sketch,object category recognition,deep learning
Computer vision,Abstraction,Computer science,Epitome,Sketch recognition,Supercomputer Education Research Centre,Artificial intelligence,Deep learning,Object category recognition,Discriminative model,Sketch
Conference
Citations 
PageRank 
References 
5
0.55
19
Authors
2
Name
Order
Citations
PageRank
Ravi Kiran Sarvadevabhatla178.41
R. Venkatesh Babu2104684.83