A histogram-based method for detection of faces and cars

Author

Schneiderman, Henry ; Kanade, Takeo

Author_Institution

Robotics Inst., Carnegie Mellon Univ., Pittsburgh, PA, USA

Volume

3

fYear

2000

fDate

2000

Firstpage

504

Abstract

We describe a statistical method for 3D object detection. We represent the statistics of both object appearance and “non-object” appearance using a product of histograms. Each histogram represents the joint statistics of a subset of wavelet coefficients and their position on the object. Our approach is to use many such histograms representing a wide variety of visual attributes. Using this method, we have developed the first algorithm that can reliably detect human faces that vary from frontal view to full profile view and the first algorithm that can reliably detect cars over a wide range of viewpoints

Keywords

image representation; object detection; statistical analysis; wavelet transforms; 3D object detection; algorithm; car detection; face detection; frontal view; full profile view; histogram-based method; histograms product; joint statistics; nonobject appearance; object appearance; statistical method; visual attributes representation; wavelet coefficient; Detectors; Face detection; Histograms; Humans; Object detection; Robots; Statistical analysis; Statistical distributions; Statistics; Wavelet coefficients;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 2000. Proceedings. 2000 International Conference on

Conference_Location

Vancouver, BC

ISSN

1522-4880

Print_ISBN

0-7803-6297-7

Type

conf

DOI

10.1109/ICIP.2000.899473

Filename

899473