Advanced Video-Based Surveillance
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Citation: EURASIP Journal on Image and Video Processing 2011 2011:857084
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Background Subtraction via Robust Dictionary Learning
We propose a learning-based background subtraction approach based on the theory of sparse representation and dictionary learning. Our method makes the following two important assumptions: (1) the background of...
Citation: EURASIP Journal on Image and Video Processing 2011 2011:972961 -
Automatic Reasoning about Causal Events in Surveillance Video
We present a new method for explaining causal interactions among people in video. The input to the overall system is video in which people are low/medium resolution. We extract and maintain a set of qualitativ...
Citation: EURASIP Journal on Image and Video Processing 2011 2011:530325 -
Three Novell Analog-Domain Algorithms for Motion Detection in Video Surveillance
As to reduce processing load for video surveillance embedded systems, three low-level motion detection algorithms to be implemented on an analog CMOS image sensor are presented. Allowing on-chip segmentation o...
Citation: EURASIP Journal on Image and Video Processing 2011 2011:698914 -
Static Object Detection Based on a Dual Background Model and a Finite-State Machine
Detecting static objects in video sequences has a high relevance in many surveillance applications, such as the detection of abandoned objects in public areas. In this paper, we present a system for the detect...
Citation: EURASIP Journal on Image and Video Processing 2010 2011:858502 -
BigBackground-Based Illumination Compensation for Surveillance Video
Illumination changes cause challenging problems for video surveillance algorithms, as objects of interest become masked by changes in background appearance. It is desired for such algorithms to maintain a cons...
Citation: EURASIP Journal on Image and Video Processing 2010 2011:171363 -
Co-Occurrence of Local Binary Patterns Features for Frontal Face Detection in Surveillance Applications
Face detection in video sequence is becoming popular in surveillance applications. The tradeoff between obtaining discriminative features to achieve accurate detection versus computational overhead of extracti...
Citation: EURASIP Journal on Image and Video Processing 2010 2011:745487 -
Face Recognition from Still Images to Video Sequences: A Local-Feature-Based Framework
Although automatic faces recognition has shown success for high-quality images under controlled conditions, for video-based recognition it is hard to attain similar levels of performance. We describe in this p...
Citation: EURASIP Journal on Image and Video Processing 2010 2011:790598 -
Contextual Information and Covariance Descriptors for People Surveillance: An Application for Safety of Construction Workers
In computer science, contextual information can be used both to reduce computations and to increase accuracy. This paper discusses how it can be exploited for people surveillance in very cluttered environments...
Citation: EURASIP Journal on Image and Video Processing 2010 2011:684819 -
Motion Pattern Extraction and Event Detection for Automatic Visual Surveillance
Efficient analysis of human behavior in video surveillance scenes is a very challenging problem. Most traditional approaches fail when applied in real conditions and contexts like amounts of persons, appearanc...
Citation: EURASIP Journal on Image and Video Processing 2010 2011:163682 -
Camera Network Coverage Improving by Particle Swarm Optimization
This paper studies how to improve the field of view (FOV) coverage of a camera network. We focus on a special but practical scenario where the cameras are randomly scattered in a wide area and each camera may ...
Citation: EURASIP Journal on Image and Video Processing 2010 2011:458283 -
Integrating the Projective Transform with Particle Filtering for Visual Tracking
This paper presents the projective particle filter, a Bayesian filtering technique integrating the projective transform, which describes the distortion of vehicle trajectories on the camera plane. The characte...
Citation: EURASIP Journal on Image and Video Processing 2010 2011:839412 -
A Low-Complexity Algorithm for Static Background Estimation from Cluttered Image Sequences in Surveillance Contexts
For the purposes of foreground estimation, the true background model is unavailable in many practical circumstances and needs to be estimated from cluttered image sequences. We propose a sequential technique f...
Citation: EURASIP Journal on Image and Video Processing 2010 2011:164956 -
AUTO GMM-SAMT: An Automatic Object Tracking System for Video Surveillance in Traffic Scenarios
A complete video surveillance system for automatically tracking shape and position of objects in traffic scenarios is presented. The system, called Auto GMM-SAMT, consists of a detection and a tracking unit. T...
Citation: EURASIP Journal on Image and Video Processing 2010 2011:814285 -
3D Objects Localization Using Fuzzy Approach and Hierarchical Belief Propagation: Application at Level Crossings
Technological solutions for obstacle-detection systems have been proposed to prevent accidents in safety-transport applications. In order to avoid the limits of these proposed technologies, an obstacle-detecti...
Citation: EURASIP Journal on Image and Video Processing 2010 2011:548604 -
Behavioural Analysis with Movement Cluster Model for Concurrent Actions
We present an approach to model articulated human movements and to analyse their behavioural semantics. First, we describe a novel dynamic and behavioural model that uses movements, a sequence of consecutive p...
Citation: EURASIP Journal on Image and Video Processing 2010 2011:365307