Visual motion based behavior learning using hierarchical discriminant regression
Pattern Recognition Letters
The Background Subtraction Problem for Video Surveillance Systems
RobVis '01 Proceedings of the International Workshop on Robot Vision
Real-time thresholding with Euler numbers
Pattern Recognition Letters
Foreground object detection from videos containing complex background
MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
Reliable real-time foreground detection for video surveillance applications
Proceedings of the third ACM international workshop on Video surveillance & sensor networks
Detecting moving people in video streams
Pattern Recognition Letters
Segmentation and tracking of multiple video objects
Pattern Recognition
Machine Vision and Applications
Video Object Segmentation Based on Feedback Schemes Guided by a Low-Level Scene Ontology
ACIVS '08 Proceedings of the 10th International Conference on Advanced Concepts for Intelligent Vision Systems
Detection and segmentation of moving objects in complex scenes
Computer Vision and Image Understanding
SIP '07 Proceedings of the Ninth IASTED International Conference on Signal and Image Processing
Multiscale background modelling and segmentation
DSP'09 Proceedings of the 16th international conference on Digital Signal Processing
Real-time FPGA architecture of modified stable Euler-number algorithm for image binarization
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
An object-based change detection approach by integrating intensity and texture differences
CAR'10 Proceedings of the 2nd international Asia conference on Informatics in control, automation and robotics - Volume 3
A robust fusion method for vehicle detection in road traffic surveillance
ICIC'10 Proceedings of the Advanced intelligent computing theories and applications, and 6th international conference on Intelligent computing
Robust and efficient change detection algorithm
AMT'10 Proceedings of the 6th international conference on Active media technology
Hand detection and gesture recognition exploit motion times image in complicate scenarios
ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part II
A hybrid color-based foreground object detection method for automated marine surveillance
ACIVS'05 Proceedings of the 7th international conference on Advanced Concepts for Intelligent Vision Systems
An autonomous surveillance vehicle for people tracking
ICIAP'05 Proceedings of the 13th international conference on Image Analysis and Processing
Detection of noise in digital images by using the averaging filter name COV
ACIIDS'13 Proceedings of the 5th Asian conference on Intelligent Information and Database Systems - Volume Part II
Dynamic saliency models and human attention: a comparative study on videos
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part III
Modified stable Euler-number algorithm implementation for real-time image binarization
Journal of Real-Time Image Processing
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Image differencing is used for many applications involving change detection. Although it is usually followed by a thresholding operation to isolate regions of change there are few methods available in the literature specific to (and appropriate for) change detection. We describe four different methods for selecting thresholds that work on very different principles. Either the noise or the signal is modelled, and the model covers either the spatial or intensity distribution characteristics. The methods are: 1/ a Normal model is used for the noise intensity distribution, 2/ signal intensities are tested by making local intensity distribution comparisons in the two image frames (i.e. the difference map is not used), 3/ the spatial properties of the noise are modelled by a Poisson distribution, and 4/ the spatial properties of the signal are modelled as a stable number of regions (or stable Euler number).