Vehicle Flow Detection Using Fast Region Matching with Adaptive Gaussian Mixture Background Model

Hui Ding

doi:10.4028/www.scientific.net/AMR.108-111.1272

Paper Titles

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Research on Trust Model Based on Behavior and Trusted Computing
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An Empirical Study on Predicting Financial Risk of Listed Companies
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Vehicle Flow Detection Using Fast Region Matching with Adaptive Gaussian Mixture Background Model
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Identification of Chaotic Characteristics of Rural Energy Consumption in China Based on GA and Neural Network
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Study of User Activity in Peer to Peer Living Streaming System
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Optimization of ARQ Mechanism in Wireless Relay Network
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The Concave Contour Detection Based on GVFsnake
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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 108-111Vehicle Flow Detection Using Fast Region Matching...

Vehicle Flow Detection Using Fast Region Matching with Adaptive Gaussian Mixture Background Model

Abstract:

Video surveillance play an important role in many ITS. In this paper, we present a fast and reliable algorithm for detecting traffic flow count. The core of the algorithm relies on Gaussian mixture background model combined fast cross-correlation region-based techniques in moving object matching. By working with adaptive Gaussian mixture model, obtained the moving vehicle as foreground. Then, fast local correlation, referred to as single matching phase, is achieved by using recursive computation schemes, which enabled us to minimize the amount of calculations required at every new pixel. We have tested our match algorithm in a large set of experiments with video clips and achieved good matching results.

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Periodical:

Advanced Materials Research (Volumes 108-111)

Pages:

1272-1277

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.108-111.1272

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Online since:

May 2010

Authors:

Hui Ding

Keywords:

Gaussian Mixture Model, Region Matching, Vehicle Flow Detection, Video Analysis

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