In this paper, we present a new method for detecting visual objects in digital images and video. The novelty of the proposed method is that it differentiates objects from non-objects using image edge characteristics. Our approach is based on a fast object detection method developed by Viola and Jones. While Viola and Jones use Harr-like features, we propose a new image feature -the edge density -that can be computed more efficiently. When applied to the problem of detecting people and pedestrians in images, the new feature shows a very good discriminative capability compared to the Harr-like features.
Son Lam Phung and Abdesselam Bouzerdoum REF explained a similar kind of approach based on edge density for detecting peoples and they expressed a new image feature for fast detection of people in Images.
Detecting People in Images: An Edge Density Approach
2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07
2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07
Computer Science