Title :
Automated audience polling on iPhone
Author :
Heidari, Alireza ; Aarabi, P.
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Toronto, Toronto, ON, Canada
Abstract :
A system for the automatic visual estimation of in-class polling using an iPhone is proposed which detects the number of faces within the field of view, the number of raised hands within the field of view, and uses the ratio as the estimate of the number of positive votes. The system utilizes the Adaboost object detection algorithm implemented in OpenCV, and processes all detected faces and raised hands, to determine whether each of the audience available in the scene are voting or not. Several examples with actual iPhone images are shown in order to illustrate the utility of the proposed system.
Keywords :
computer vision; face recognition; learning (artificial intelligence); object detection; smart phones; Adaboost object detection algorithm; OpenCV; automated audience polling; automatic visual estimation; face detection; field of view; iPhone images; in-class polling; Computers; Detectors; Face detection; Object detection; Training; Visualization; Audience polling; iPhone programming; object detection;
Conference_Titel :
Electrical and Computer Engineering (CCECE), 2013 26th Annual IEEE Canadian Conference on
Conference_Location :
Regina, SK
Print_ISBN :
978-1-4799-0031-2
Electronic_ISBN :
0840-7789
DOI :
10.1109/CCECE.2013.6567814
