Region-based parametric motion segmentation using color information
Graphical Models and Image Processing
Object Tracking with Bayesian Estimation of Dynamic Layer Representations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Video sequence segmentation using genetic algorithms
Pattern Recognition Letters
Optic Flow Field Segmentation and Motion Estimation Using a Robust Genetic Partitioning Algorithm
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Real-Time Region-Based Motion Segmentation Using Adaptive Thresholding and K-Means Clustering
AI '01 Proceedings of the 14th Australian Joint Conference on Artificial Intelligence: Advances in Artificial Intelligence
Optical flow estimation and moving object segmentation based on median radial basis function network
IEEE Transactions on Image Processing
Statistical change detection with moments under time-varying illumination
IEEE Transactions on Image Processing
Centre of mass model - A novel approach to background modelling for segmentation of moving objects
Image and Vision Computing
Generation of Multiple Background Model by Estimated Camera Motion Using Edge Segments
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues
3D Neural Model-Based Stopped Object Detection
ICIAP '09 Proceedings of the 15th International Conference on Image Analysis and Processing
A 3D Neural Model for Video Analysis
Proceedings of the 2009 conference on Neural Nets WIRN09: Proceedings of the 19th Italian Workshop on Neural Nets, Vietri sul Mare, Salerno, Italy, May 28--30 2009
Moving object segmentation by background subtraction and temporal analysis
Image and Vision Computing
Auto-surveillance for object to bring in/out using multiple camera
ICIC'09 Proceedings of the 5th international conference on Emerging intelligent computing technology and applications
A multi-layer scene model for video surveillance applications
PCM'10 Proceedings of the 11th Pacific Rim conference on Advances in multimedia information processing: Part I
Real-time stopped object detection by neural dual background modeling
Euro-Par 2010 Proceedings of the 2010 conference on Parallel processing
Advances in background updating and shadow removing for motion detection algorithms
CAIP'05 Proceedings of the 11th international conference on Computer Analysis of Images and Patterns
A moving detection algorithm based on space-time background difference
ICIC'05 Proceedings of the 2005 international conference on Advances in Intelligent Computing - Volume Part I
| Hi-index | 0.10 |
This paper describes a new method to detect moving objects in a dynamic scene based on background subtraction. The main goal of the method is to obtain and keep a stable background image to cope with variations on environmental changing conditions. In this way, we use a double background (long-term background and short-term background) to deal with temporal stability and fast changes. In addition, this method computes the temporal changes in the video sequence by a local convolution mask taking into account the information of the pixel neighborhood, being less sensitive to noise. Besides, the method classifies the regions of change in moving and static blobs. The first ones represent real moving objects, and the second are related to illumination changes and noise. Finally, experimental results and a performance measure establishing the confidence of the method are presented.