Automatic Person Identification in Camera Video by Motion Correlation

Joint Authors

Duan, Dingbo
Gao, Guangyu
Liu, Chi Harold
Ma, Jian

Source

Journal of Sensors

Issue

Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-8, 8 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2014-06-03

Country of Publication

Egypt

No. of Pages

8

Main Subjects

Civil Engineering

Abstract EN

Person identification plays an important role in semantic analysis of video content.

This paper presents a novel method to automatically label persons in video sequence captured from fixed camera.

Instead of leveraging traditional face recognition approaches, we deal with the task of person identification by fusing information from motion sensor platforms, like smart phones, carried on human bodies and extracted from camera video.

More specifically, a sequence of motion features extracted from camera video are compared with each of those collected from accelerometers of smart phones.

When strong correlation is detected, identity information transmitted from the corresponding smart phone is used to identify the phone wearer.

To test the feasibility and efficiency of the proposed method, extensive experiments are conducted which achieved impressive performance.

American Psychological Association (APA)

Duan, Dingbo& Gao, Guangyu& Liu, Chi Harold& Ma, Jian. 2014. Automatic Person Identification in Camera Video by Motion Correlation. Journal of Sensors،Vol. 2014, no. 2014, pp.1-8.
https://search.emarefa.net/detail/BIM-1042985

Modern Language Association (MLA)

Duan, Dingbo…[et al.]. Automatic Person Identification in Camera Video by Motion Correlation. Journal of Sensors No. 2014 (2014), pp.1-8.
https://search.emarefa.net/detail/BIM-1042985

American Medical Association (AMA)

Duan, Dingbo& Gao, Guangyu& Liu, Chi Harold& Ma, Jian. Automatic Person Identification in Camera Video by Motion Correlation. Journal of Sensors. 2014. Vol. 2014, no. 2014, pp.1-8.
https://search.emarefa.net/detail/BIM-1042985

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1042985