DocumentCode
3420088
Title
How Do You Tell a Blackbird from a Crow?
Author
Berg, Thomas ; Belhumeur, Peter N.
fYear
2013
fDate
1-8 Dec. 2013
Firstpage
9
Lastpage
16
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.
Keywords
feature extraction; image recognition; automatic recognition systems; bird images; blackbird; crow; fine-grained visual categorization; visual features; visual recognition; Beak; Birds; Feature extraction; Image color analysis; Vectors; Vegetation; Visualization; field guide; fine-grained recognition; visual similarity;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision (ICCV), 2013 IEEE International Conference on
Conference_Location
Sydney, VIC
ISSN
1550-5499
Type
conf
DOI
10.1109/ICCV.2013.9
Filename
6751110
Link To Document