Image Classification Between Two Animals

We are going to examine the fine-grained object categorization problem of identifying the breed of animal from a picture. To this end we introduce a replacement annotated dataset of pets covering 37 different breeds of cats and dogs. The visual problem is extremely challenging for the cat and dog, particularly cats, are very deformable and there are often exactly subtle differences between their breeds. We make variety of contributions: we first introduce a model to classify cat and dog breed automatically from a picture. The model adding the shape of the pet animals, captured by a deformable part model detecting the cat and dog face, and appearance, captured by a bag-of-words model that describes the pet fur. Fitting the model involves automatically segmenting the cat and dog within the image. Second, we compare two classification approaches: a hierarchical one, during which a pet animal is first assigned to the cat or dog family then to a breed, and a flat one, during which the breed is obtained directly.