Cats and dogs
International Institute of Information Technology, Hyderabad · University of Oxford
Abstract
We investigate the fine grained object categorization problem of determining the breed of animal from an image. To this end we introduce a new annotated dataset of pets covering 37 different breeds of cats and dogs. The visual problem is very challenging as these animals, particularly cats, are very deformable and there can be quite subtle differences between the breeds. We make a number of contributions: first, we introduce a model to classify a pet breed automatically from an image. The model combines shape, captured by a deformable part model detecting the pet face, and appearance, captured by a bag-of-words model that describes the pet fur. Fitting the model involves automatically segmenting the animal in…
Citation impact
- FWCI
- 26.35
- Percentile
- 100%
- References
- 39
Authors
4Topics & keywords
- Breed
- Categorization
- Artificial intelligence
- Computer science
- Pattern recognition (psychology)
- Face (sociological concept)
- Segmentation
- CATS
- Reduced inequalities