A Robust Technique for Background Subtraction and Shadow Elimination in Traffic Video Sequence

2009 ◽  
pp. 311-322 ◽  
Author(s):  
Tao Gao ◽  
Zheng-guang Liu ◽  
Wen-chun Gao ◽  
Jun Zhang
Keyword(s):  
Background Subtraction ◽  
Video Sequence ◽  
Shadow Elimination ◽  
Traffic Video

Robust background subtraction in traffic video sequence

2010 ◽  
Vol 17 (1) ◽  
pp. 187-195 ◽  
Author(s):  
Tao Gao ◽  
Zheng-guang Liu ◽  
Shi-hong Yue ◽  
Jun Zhang ◽  
Jian-qiang Mei ◽  
...  
Keyword(s):  
Background Subtraction ◽  
Video Sequence ◽  
Traffic Video

Block Background Subtraction Method Based on ViBe

2014 ◽  
Vol 556-562 ◽  
pp. 3549-3552
Author(s):  
Lian Fen Huang ◽  
Qing Yue Chen ◽  
Jin Feng Lin ◽  
He Zhi Lin
Keyword(s):  
Spatial Correlation ◽  
Background Subtraction ◽  
Video Sequence ◽  
Moving Objects ◽  
Moving Object ◽  
Background Model ◽  
Subtraction Method ◽  
Current Frame ◽  
The Difference ◽  
Set Up

The key of background subtraction which is widely used in moving object detecting is to set up and update the background model. This paper presents a block background subtraction method based on ViBe, using the spatial correlation and time continuity of the video sequence. Set up the video sequence background model firstly. Then, update the background model through block processing. Finally employ the difference between the current frame and background model to extract moving objects.

Image Texture-Based Vehicle Cast Shadow Elimination Approach

2014 ◽  
Vol 644-650 ◽  
pp. 1066-1069
Author(s):  
Dong Mei Zhou ◽  
Ming Xing Zhang ◽  
Yong Xia Dai
Keyword(s):  
Video Sequence ◽  
New Method ◽  
Image Texture ◽  
Transport Systems ◽  
Shadow Removal ◽  
Intelligent Transport Systems ◽  
Intelligent Transport ◽  
Shadow Elimination ◽  
Cast Shadow ◽  
Vehicle Information

Based on the research and analysis of video sequence of the Intelligent Transport Systems,this paper especially had a in-depth discussion about the critical step of video detection—shadow removing, analyzing the causes and characteristics of the shadow,describing the current shadow removal algorithms,and proposed a new method of image texture-based vehicle cast shadow elimination approach based on the existing algorithms.Experimental results have proved that this method can remove the vehicle shadow well and still hold very complete target vehicle information and laid the foundation for extracting vehicle target.

scholarly journals Shadow Elimination in Soccer Game Video using Background Subtraction and Sobel Operators

2020 ◽  
pp. 2426-2433
Author(s):  
Huda Dheyauldeen Najeeb ◽  
Rana Fareed Ghani
Keyword(s):  
Real Time ◽  
Background Subtraction ◽  
Challenging Problem ◽  
Shadow Elimination ◽  
Ball Size ◽  
Soccer Game ◽  
Wide Range ◽  
Similar Appearance ◽  
New System ◽  
Sobel Operators

Object detection in real time is considered as a challenging problem. However, it is very important in a wide range of applications, especially in field of multimedia. The players and ball are the most important objects in soccer game videos and detecting them is a challenging task because of many difficulties, such as shadow and illumination, ball size, ball occluded by players or merged with lines, and similar appearance of players. To overcome these problems, we present a new system to detect the players and ball in real-time by using background subtraction and Sobel detection. The results were more accurate and approximately two times faster than those using only background subtraction.

scholarly journals AN ADAPTIVE BACKGROUND UPDATION AND GRADIENT BASED SHADOW REMOVAL METHOD

2013 ◽  
pp. 288-293
Author(s):  
SUMIT KUMAR SINGH ◽  
MAGAN SINGH
Keyword(s):  
Background Subtraction ◽  
Moving Objects ◽  
Object Segmentation ◽  
Moving Object ◽  
Shadow Removal ◽  
Subtraction Method ◽  
Moving Object Segmentation ◽  
Shadow Elimination ◽  
Illumination Changes ◽  
Gradient Based

Moving object segmentation has its own niche as an important topic in computer vision. It has avidly being pursued by researchers. Background subtraction method is generally used for segmenting moving objects. This method may also classify shadows as part of detected moving objects. Therefore, shadow detection and removal is an important step employed after moving object segmentation. However, these methods are adversely affected by changing environmental conditions. They are vulnerable to sudden illumination changes, and shadowing effects. Therefore, in this work we propose a faster, efficient and adaptive background subtraction method, which periodically updates the background frame and gives better results, and a shadow elimination method which removes shadows from the segmented objects with good discriminative power. Keywords- Moving object segmentation,

Research on Vehicle Detection and Shadow Elimination Based on Static Image Sequence

2014 ◽  
Vol 602-605 ◽  
pp. 2362-2365
Author(s):  
Quan Wu Li ◽  
Yu Hui Li ◽  
Bo Li ◽  
Yi Chen
Keyword(s):  
Edge Detection ◽  
Background Subtraction ◽  
Vehicle Detection ◽  
Image Sequence ◽  
Background Modeling ◽  
High Definition ◽  
Canny Edge Detection ◽  
New Approach ◽  
Shadow Elimination ◽  
Canny Edge

Focused on static high-definition sequence images captured on the highway bayonet, this paper proposes a new approach for vehicle detection and shadow elimination based on average background modeling, which uses average background model and background subtraction to locate vehicle roughly, eliminates shadow of the vehicle using canny edge detection with dynamic histogram threshold determined by the histogram of the image. Experiments show that this method can locate the position of vehicle quickly and accurately.

scholarly journals HYBRID APPROACH FOR KEY FRAME EXTRACTION FROM VIDEO SEQUENCE

2017 ◽  
Vol 5 (4RACSIT) ◽  
pp. 97-104
Author(s):  
Satish Kumar
Keyword(s):  
Background Subtraction ◽  
Video Sequence ◽  
State Of The Art ◽  
Hybrid Approach ◽  
Considerable Improvement ◽  
Video Sequences ◽  
Key Frame ◽  
Key Frames ◽  
Mixture Of Gaussian ◽  
Fine Tune

This paper proposed and developed hybrid approach for extraction of key-frames from video sequences from stationary camera. This method first uses histogram difference to extract the candidate key frames from the video sequences, later using Background subtraction algorithm (Mixture of Gaussian) was used to fine tune the final key frames from the video sequences. This developed approach show considerable improvement over the state-of-the art techniques and same is reported in this paper.

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