Silhouette based human motion detection and analysis for real-time automated video surveillance

EKINCI, MURAT; Gedikli, Eyup

Silhouette based human motion detection and analysis for real-time automated video surveillance

Murat EKİNCİ, (Karadeniz Teknik Üniversitesi, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü, Trabzon, Türkiye)

Eyüp GEDİKLİ (Karadeniz Teknik Üniversitesi, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü, Trabzon, Türkiye)

Turkish Journal of Electrical Engineering and Computer Sciences

4 0

Yıl: 2005 Cilt: 13 Sayı: 2 Sayfa Aralığı: 199 - 229 Metin Dili: İngilizce İndeks Tarihi: 29-07-2022

Silhouette based human motion detection and analysis for real-time automated video surveillance

Öz:

In this paper, a real-time background modeling and maintenance based human motion detection and analysis in an indoor and an outdoor environments for visual surveillance system is described. The system operates on monocular gray scale video imagery from a static CCD camera. In order to detect foreground objects, first, background scene model is statistically learned using the redundancy of the pixel intensities in a training stage, even the background is not completely stationary. This redundancy information of the each pixel is separately stored in an history map shows how the pixel intensity values changes till now. Then the highest ratio of the redundancy on the pixel intensity values in the history map in the training sequence is determined to have initial background model of the scene. A background maintenance model is also proposed for preventing some kind of falsies, such as, illumination changes (the sun being blocked by clouds causing changes in brightness), or physical changes (person detection while he is getting out or passing in front of the parked car). At the background modeling and maintenance, the reliability and computational costs of the algorithm presented are comparatively discussed with several algorithms. Based on the background modeling, candidate foreground regions are detected using thresholding, noise cleaning and their boundaries extracted using morphological filters. Then for people detection, object detection and classification approach for distinguishing a person, a group of person from detected foreground objects (e.g., cars) using silhouette shape and periodic motion cues is performed. Finally, the trajectory of the people in motion and several motion parameters produced from the cyclic motion of silhouette of the object under tracking are implemented for analyzing people activities such as walking and running, in the video sequences. Experimental results on the different test image sequences demonstrate that the proposed algorithm has an encouraging real-time background modeling based human motion detection and analysis performance with relatively robust and low computational cost.

Anahtar Kelime:

Konular: Mühendislik, Elektrik ve Elektronik

Belge Türü: Makale Makale Türü: Araştırma Makalesi Erişim Türü: Erişime Açık

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APA	EKINCI M, Gedikli E (2005). Silhouette based human motion detection and analysis for real-time automated video surveillance. , 199 - 229.
Chicago	EKINCI MURAT,Gedikli Eyup Silhouette based human motion detection and analysis for real-time automated video surveillance. (2005): 199 - 229.
MLA	EKINCI MURAT,Gedikli Eyup Silhouette based human motion detection and analysis for real-time automated video surveillance. , 2005, ss.199 - 229.
AMA	EKINCI M,Gedikli E Silhouette based human motion detection and analysis for real-time automated video surveillance. . 2005; 199 - 229.
Vancouver	EKINCI M,Gedikli E Silhouette based human motion detection and analysis for real-time automated video surveillance. . 2005; 199 - 229.
IEEE	EKINCI M,Gedikli E "Silhouette based human motion detection and analysis for real-time automated video surveillance." , ss.199 - 229, 2005.
ISNAD	EKINCI, MURAT - Gedikli, Eyup. "Silhouette based human motion detection and analysis for real-time automated video surveillance". (2005), 199-229.

APA	EKINCI M, Gedikli E (2005). Silhouette based human motion detection and analysis for real-time automated video surveillance. Turkish Journal of Electrical Engineering and Computer Sciences, 13(2), 199 - 229.
Chicago	EKINCI MURAT,Gedikli Eyup Silhouette based human motion detection and analysis for real-time automated video surveillance. Turkish Journal of Electrical Engineering and Computer Sciences 13, no.2 (2005): 199 - 229.
MLA	EKINCI MURAT,Gedikli Eyup Silhouette based human motion detection and analysis for real-time automated video surveillance. Turkish Journal of Electrical Engineering and Computer Sciences, vol.13, no.2, 2005, ss.199 - 229.
AMA	EKINCI M,Gedikli E Silhouette based human motion detection and analysis for real-time automated video surveillance. Turkish Journal of Electrical Engineering and Computer Sciences. 2005; 13(2): 199 - 229.
Vancouver	EKINCI M,Gedikli E Silhouette based human motion detection and analysis for real-time automated video surveillance. Turkish Journal of Electrical Engineering and Computer Sciences. 2005; 13(2): 199 - 229.
IEEE	EKINCI M,Gedikli E "Silhouette based human motion detection and analysis for real-time automated video surveillance." Turkish Journal of Electrical Engineering and Computer Sciences, 13, ss.199 - 229, 2005.
ISNAD	EKINCI, MURAT - Gedikli, Eyup. "Silhouette based human motion detection and analysis for real-time automated video surveillance". Turkish Journal of Electrical Engineering and Computer Sciences 13/2 (2005), 199-229.