Using-a-Boosted-Cascade.rar_SVM检测目标_cascade_hog+SVM_目标检测_行人检测

MITSUBISHI ELECTRIC RESEARCH LABORATORIES

http://www.merl.com

Rapid Object Detection Using a Boosted

Cascade of Simple Features

Viola, P.; Jones, M.

TR2004-043 May 2004

Abstract

This paper describes a machine learning approach for visual object detection which is capable

of processing images extremely rapidly and achieving high detection rates. This work is distin-

computation on promising object-like regions. The cascade can be viewed as an object specific

focus-of-attention mechanism which unlike previous approaches provides statistical guarantees

that discarded regions are unlikely to contain the object of interest. In the domain of face detec-

tion the system yields detection rates comparable to the best previous systems. Used in real-time

applications, the detector runs at 15 frames per second without resorting to image differencing

or skin color detection.

IEEE Computer Society Conference on Computer Vision and Pattern Recognition

This work may not be copied or reproduced in whole or in part for any commercial purpose. Permission to copy in whole or in part

without payment of fee is granted for nonprofit educational and research purposes provided that all such whole or partial copies include

the following: a notice that such copying is by permission of Mitsubishi Electric Research Laboratories, Inc.; an acknowledgment of

http://www.merl.com

Rapid Object Detection Using a Boosted

Cascade of Simple Features

Paul Viola and Michael Jones

TR-2004-043 May 2004

Abstract

This paper describes a machine learning approach for visual object detection which is capable

of processing images extremely rapidly and achieving high detection rates. This work is distin-

guished by three key contributions. The first is the introduction of a new image representation

focus-of-attention mechanism which unlike previous approaches provides statistical guarantees

that discarded regions are unlikely to contain the object of interest. In the domain of face detec-

tion the system yields detection rates comparable to the best previous systems. Used in real-time

applications, the detector runs at 15 frames per second without resorting to image differencing

or skin color detection.

This work may not be copied or reproduced in whole or in part for any commercial purpose. Permission to copy in whole or in part

without payment of fee is granted for nonprofit educational and research purposes provided that all such whole or partial copies include

the following: a notice that such copying is by permission of Mitsubishi Electric Research Laboratories, Inc.; an acknowledgment of

the authors and individual contributions to the work; and all applicable portions of the copyright notice. Copying, reproduction, or

republishing for any other purpose shall require a license with payment of fee to Mitsubishi Electric Research Laboratories, Inc. All

Publication History: