Incremental recognition of pedestrians from image sequences

Author

Rohr, K.

Author_Institution

FB Inf., Hamburg Univ., Germany

fYear

1993

fDate

15-17 Jun 1993

Firstpage

8

Lastpage

13

Abstract

An approach that uses a volume model consisting of cylinders for model-based recognition of pedestrians in real-world images is presented. The human body is represented by a volume model, and medical motion data are used for simulating the movement of walking. This knowledge is exploited to determine the 3-D position, as well as the posture of an observed person. By applying a Kalman filter, the model parameters in consecutive images are incrementally estimated. The approach is tested on real image data

Keywords

Kalman filters; biomechanics; filtering theory; image recognition; image sequences; parameter estimation; 3-D position; Kalman filter; cylinders; gait analysis; image sequences; incremental recognition; medical motion data; model-based recognition; parameter estimation; pedestrian recognition; real-world images; volume model; walking; Biological system modeling; Biomedical imaging; Clothing; Humans; Image recognition; Image sequences; Joints; Legged locomotion; Medical diagnostic imaging; Medical simulation; Parameter estimation; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Vision and Pattern Recognition, 1993. Proceedings CVPR '93., 1993 IEEE Computer Society Conference on

Conference_Location

New York, NY

ISSN

1063-6919

Print_ISBN

0-8186-3880-X

Type

conf

DOI

10.1109/CVPR.1993.341008

Filename

341008