Using Adaboost Method for Face Detection and Pedestrian-Flow Evaluation of Digital Signage

Author

Shye-Chorng Kuo ; Cheng-Jian Lin ; Chun-Cheng Peng

Author_Institution

Dept. of Multimedia Animation & Applic., Nan Kai Univ. of Technol., TsaoTun, Taiwan

fYear

2014

fDate

10-12 June 2014

Firstpage

90

Lastpage

93

Abstract

Within modern society, digital signage, billboards, and signboards have been widely and successfully applied for sending various information and advertisement. However, how to evaluate the dispatched benefits is an extremely important issue for business owners. In order to tackle this problem, this paper proposes an effective evaluating system for digital billboard audiences. Via the build-in front-end camera, individual audiences´ watched dates, time periods, halted durations and locations are able to be precisely recorded, and through these collected data the proposed evaluation system can provide statistical information to the authorized personnel for further assessing the relative benefits of specific billboard.

Keywords

advertising data processing; face recognition; learning (artificial intelligence); object detection; statistical analysis; Adaboost method; billboard benefits; digital billboard audiences; digital signage; face detection; front-end camera; pedestrian-flow evaluation; signboards; statistical information; Classification algorithms; Face; Face detection; Feature extraction; Filtering; Object detection; Personnel; Adaboost; Advertisement benefit evaluation; digital billboard; human face detection; pedestrian-flow statistics;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer, Consumer and Control (IS3C), 2014 International Symposium on

Conference_Location

Taichung

Type

conf

DOI

10.1109/IS3C.2014.35

Filename

6845467