ISBN: 978-981-09-5471-0 DOI: 10.18178/wcse.2015.04.036
Video Based Adult and Child Classification by Using Body Proportion
Abstract— Pedestrian detection in uncontrolled environments is a challenging task. There are
various researches for video based pedestrian detection. Moreover, to recognize children and adults
in digital platforms is helpful for future applications. For instance, if a Closed Circuit
Television(CCTV) camera located on a traffic light detects child who is walking through pedestrian
way, system could make some service adjustments. Aim of this article is to detect children and
adults separately. We used Haar cascade classifiers for the implementation. We detected head and
body of pedestrians. Then we used relative measurements because we cannot get exact height of
people from pixels so we applied another method that is proportioning head size to body size of
pedestrians. By this technique, we could discriminate children and adults. The results are promising
and shows sufficient accuracy.
Index Terms— haar-like feature, biometric evaluation, adult and child classification.
Omer F. Ince, M. Eren Yildirim, J.S. Park, J.Song, B.W. Yoon
Department of Electronics Engineering, Kyungsung University, KOREA
Cite: Omer F. Ince, M. Eren Yildirim, J.S. Park, J.Song, B.W. Yoon, "Video Based Adult and Child Classification by Using Body Proportion," 2015 The 5th International Workshop on Computer Science and Engineering-Information Processing and Control Engineering (WCSE 2015-IPCE), pp. 220-223, Moscow, Russia, April 15-17, 2015.