The goal of this paper is to offer a framework for classification of images and video according to their "type", or "style" - a problem which is hard to define, but easy to illustrate; for example, identifying an artist by the style of his/her painting, or determining the activity in a video sequence. The paper offers a simple classification paradigm based on local properties of spatial or spatio-temporal blocks. The learning and classification are based on the naive Bayes classifier. A few experimental results are presented.
Bibliographical noteFunding Information:
This research was supported by The Israel Science Foundation (grant no. 591/00-10.5).
- Activity detection
- Image style
- Naive Bayes
ASJC Scopus subject areas
- Signal Processing
- Computer Vision and Pattern Recognition
- Artificial Intelligence