Share Email Print
cover

Proceedings Paper

Real-time nonparametric background modeling using moving histogram method for visual surveillance
Author(s): Gyu-Dong Lee; Woong-Hee Lee; Dong-Seok Jeong
Format Member Price Non-Member Price
PDF $17.00 $21.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

The background and foreground modeling is essential in tracking objects from the scenes taken by the stationary camera. We suggest a background model using moving histogram method. A moving histogram, which can be called pixel-wise approach, is time-dependent and can be regarded as a probability density function (pdf) of intensity in image sequence. This moving histogram is updated using image sequence from a stationary camera and is used to calculate the probability of which a pixel in incoming image belongs to background model. Pixels failed in entering into the background model can be candidates for foreground objects. These pixels are classified into foreground ones by comparing with other candidate pixels in different image frames. For pixel classification, our background process consists of queue memory which stores recently acquired images. The background process updates moving histogram for each (x, y) pixel and computes maximum frequency pixel value with low computation. After updating the moving histogram, the background process classifies each pixel as the moving pixel or the background pixel. The classification is difficult because of the slow change in background brightness, slow moving objects, clutters, and the shadow. We solve this problem heuristically. The moving histogram consists of several models (multi-modal, vehicle, background, shadow, clutter). We can compute the distance between the incoming pixel value and each model. And we use threshold with Euler numbers for foreground segmentation. The background and the segmentation process need small computation and can be adapted easily to real-time system.

Paper Details

Date Published: 28 May 2004
PDF: 8 pages
Proc. SPIE 5298, Image Processing: Algorithms and Systems III, (28 May 2004); doi: 10.1117/12.526283
Show Author Affiliations
Gyu-Dong Lee, Inha Univ. (South Korea)
Woong-Hee Lee, Inha Univ. (South Korea)
Dong-Seok Jeong, Inha Univ. (South Korea)


Published in SPIE Proceedings Vol. 5298:
Image Processing: Algorithms and Systems III
Edward R. Dougherty; Jaakko T. Astola; Karen O. Egiazarian, Editor(s)

© SPIE. Terms of Use
Back to Top