Title
How Do You Tell a Blackbird from a Crow?
Abstract
How do you tell a blackbird from a crow? There has been great progress toward automatic methods for visual recognition, including fine-grained visual categorization in which the classes to be distinguished are very similar. In a task such as bird species recognition, automatic recognition systems can now exceed the performance of non-experts - most people are challenged to name a couple dozen bird species, let alone identify them. This leads us to the question, "Can a recognition system show humans what to look for when identifying classes (in this case birds)?" In the context of fine-grained visual categorization, we show that we can automatically determine which classes are most visually similar, discover what visual features distinguish very similar classes, and illustrate the key features in a way meaningful to humans. Running these methods on a dataset of bird images, we can generate a visual field guide to birds which includes a tree of similarity that displays the similarity relations between all species, pages for each species showing the most similar other species, and pages for each pair of similar species illustrating their differences.
Year
DOI
Venue
2013
10.1109/ICCV.2013.9
ICCV
Keywords
Field
DocType
similar class,bird species recognition,similar species,automatic recognition system,visual recognition,recognition system show human,fine-grained visual categorization,visual field guide,visual feature,couple dozen bird species,feature extraction,image recognition
Computer vision,Categorization,Pattern recognition,Recognition system,Computer science,Feature extraction,Visual recognition,Artificial intelligence,Visual field
Conference
Volume
Issue
ISSN
2013
1
1550-5499
Citations 
PageRank 
References 
13
0.64
19
Authors
2
Name
Order
Citations
PageRank
Thomas Berg120712.42
Peter N. Belhumeur2122421001.27