Autosoft Journal

Online Manuscript Access

The Big Data Analysis On The Camera-Based Face Image In Surveillance Cameras



In the Big-Data era, currently how to automatically realize acquisition, refining and fast retrieval of the target information in a surveillance video has become an urgent demand in the public security video surveillance field. This paper proposes a new gun-dome camera cooperative system, which solves the above problem partly. The system adopts a master-slave static panorama-variable view dual-camera cooperative video-monitoring system. In this dual-camera system the gun camera static camera) with a wide viewing -angle lenses is in charge of the pedestrian detection and the dome camera can maneuver its focus and cradle orientation to get the clear and enlarged face images. In the proposed architecture, Deformable Part Model (DPM) method realizes real-time detection of pedestrians. The look-up table method is proved feasible in a dual-camera cooperative calibration procedure, while the depth information of the moving target changes slightly. As respect to the face detection, the deep learning architecture is exploited and proves its effectiveness. Moreover, we utilize the Haar-Like feature and LQV classifier to execute the frontal face image capture. The experimental results show the effectiveness and efficiency of the dual-camera system in close-up face image acquisition.



Total Pages: 9
Pages: 123-132


Manuscript ViewPdf Subscription required to access this document

Obtain access this manuscript in one of the following ways

Already subscribed?

Need information on obtaining a subscription? Personal and institutional subscriptions are available.

Already an author? Have access via email address?


Volume: 24
Issue: 1
Year: 2018

Cite this document


Beriault, S. (2008). Multi-camera system design, calibration and 3D reconstruction for markerless motioncapture . (Thesis). School of Information Technology and Engineering, Engineering University of Ottawa, p. 146.

Dong, Rong, Bo Li, and Qi-mei Chen. "An Automatic Calibration Method for PTZ Camera in Expressway Monitoring System." 2009 WRI World Congress on Computer Science and Information Engineering (2009): n. pag. Crossref. Web.

Felzenszwalb, Pedro, David McAllester, and Deva Ramanan. "A Discriminatively Trained, Multiscale, Deformable Part Model." 2008 IEEE Conference on Computer Vision and Pattern Recognition (2008): n. pag. Crossref. Web.

Xu Z. Computer Systems Science & Engineering 30.5 (2015)

Xu, Zheng et al. "Semantic Based Representing and Organizing Surveillance Big Data Using Video Structural Description Technology." Journal of Systems and Software 102 (2015): 217-225. Crossref. Web.

Xu, Zheng et al. "The Big Data Analytics and Applications of the Surveillance System Using Video Structured Description Technology." Cluster Computing 19.3 (2016): 1283-1292. Crossref. Web.

Xu, Zheng et al. "Semantic Enhanced Cloud Environment for Surveillance Data Management Using Video Structural Description." Computing 98.1-2 (2014): 35-54. Crossref. Web.

Xu, Zheng, Chuanping Hu, and Lin Mei. "Video Structured Description Technology Based Intelligence Analysis of Surveillance Videos for Public Security Applications." Multimedia Tools and Applications 75.19 (2015): 12155-12172. Crossref. Web.


ISSN PRINT: 1079-8587
ISSN ONLINE: 2326-005X
DOI PREFIX: 10.31209
10.1080/10798587 with T&F
IMPACT FACTOR: 0.652 (2017/2018)
Journal: 1995-Present


TSI Press
18015 Bullis Hill
San Antonio, TX 78258 USA
PH: 210 479 1022
FAX: 210 479 1048