Abstract
This paper describes a new representation for people and animals, called a body plan. The representation is an organized collection of grouping hints obtained from constraints on color, texture, shape, and geometrical relations. Body plans can be learned from image data, using established statistical learning techniques. Body plans are well adapted to segmentation and recognition in complex environments, such as the huge libraries of digitized images now becoming widely available. Two specific applications of body plans are presented: an algorithm that determines whether an image depicts a scantily clad human and an algorithm that learns and uses a body plan to find pictures of horses. Both algorithms demonstrate excellent performance on large, poorly controlled input data.
| Original language | English (US) |
|---|---|
| Title of host publication | IEEE International Conference on Image Processing |
| Publisher | IEEE Comp Soc |
| Pages | 5-8 |
| Number of pages | 4 |
| Volume | 3 |
| State | Published - 1997 |
| Externally published | Yes |
| Event | Proceedings of the 1997 International Conference on Image Processing. Part 2 (of 3) - Santa Barbara, CA, USA Duration: Oct 26 1997 → Oct 29 1997 |
Other
| Other | Proceedings of the 1997 International Conference on Image Processing. Part 2 (of 3) |
|---|---|
| City | Santa Barbara, CA, USA |
| Period | 10/26/97 → 10/29/97 |
ASJC Scopus subject areas
- Computer Vision and Pattern Recognition
- Hardware and Architecture
- Electrical and Electronic Engineering