Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Real-Time Adaptive Foreground/Background Segmentation Darren E. Butler | EURASIP Journal on Applied Signal Processing 2005 14 2292-2304 2005 Hindawi Publishing Corporation Real-Time Adaptive Foreground Background Segmentation Darren E. Butler Information Security Institute Queensland University of Technology Brisbane QLD 4001 Australia Email V. Michael Bove Jr. Media Laboratory Massachusetts Institute of Technology Cambridge MA 02139 USA Em ail vmb@ Sridha Sridharan Information Security Institute Queensland University of Technology Brisbane QLD 4001 Australia Email Received 2 January 2004 Revised 8 November 2004 The automatic analysis of digital video scenes often requires the segmentation of moving objects from a static background. Historically algorithms developed for this purpose have been restricted to small frame sizes low frame rates or offline processing. The simplest approach involves subtracting the current frame from the known background. However as the background is rarely known beforehand the key is how to learn and model it. This paper proposes a new algorithm that represents each pixel in the frame by a group of clusters. The clusters are sorted in order of the likelihood that they model the background and are adapted to deal with background and lighting variations. Incoming pixels are matched against the corresponding cluster group and are classified according to whether the matching cluster is considered part of the background. The algorithm has been qualitatively and quantitatively evaluated against three other well-known techniques. It demonstrated equal or better segmentation and proved capable of processing 320 X 240 PAL video at full frame rate using only 35 -40 of a GHz Pentium 4 computer. Keywords and phrases video segmentation background segmentation real-time video processing. 1. INTRODUCTION As humans we possess an innate ability to decompose arbitrary scenes and with only a casual glance we can recognise a multitude of shapes shades and textures. In
