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This work describes a method for accurately tracking persons in indoor surveillance video stream obtained from a static camera with difficult scene properties including illumination changes and solves the major occlusion problem. First, moving objects are precisely extracted by determining its motion, for further processing. The scene illumination changes are averaged to obtain the accurate moving...
Pedestrian detection is one of the most important techniques for surveillance applications. This paper proposes an effective method for pedestrian detection in low-contrast images. The main characteristic of the proposed method is a two-stage moving object extraction. In the first stage, the watershed algorithm is used to extract multiple regions of moving objects. In the second stage, a novel criterion...
Traditional background subtraction methods perform poorly at night. In this paper, a robust method is proposed for automatic visual surveillance in low-light level environment which has quality problems of low brightness, low contrast and high-level noise. The novel method includes techniques of illumination compensation and illumination-invariant background subtraction to solve the low-quality problem...
This paper is concerned with investigating, experiencing, and validating some non classic techniques for compound moving objects analysis in successive video frames. This composite-tasks problem has so far been very`rarely' dealt with as a `single' multidirectional problem, it has always been handled as several separate unidirectional, or seldom bidirectional problems. The paper exhibits an HCI system...
This paper is concerned with investigating, experiencing, and validating a local adaptive threshold system with compound motion analysis. The motivation here is to analyze moving objects in outdoor/indoor video frames with respect to: movement detection, objects segmentation, features extraction besides DFT-based velocity computation. The underlying methodology exhibits a single correlation of the...
In recent years, the increasing demand for security in home care services has led to further improvements in surveillance activities. This paper proposes an efficient approach for motion detecting and tracking in a surveillance system based on the cellular model. The system can monitor human activities and recognize the abnormal events of an elderly man in an indoor environment. The experimental room...
We address the problem of action recognition. Our aim is to recognize single person activities in surveillance scenes. To meet the requirements of real scene action recognition, we present a compact motion representation for human activity recognition. With the employment of efficient features extracted from optical flow as the main part, together with global information, our motion representation...
This paper proposes a motion-focusing method to extract key frames and generate summarization synchronously for surveillance videos. Within each pre-segmented video shot, the proposed method focuses on one constant-speed motion and aligns the video frames by fixing this focused motion into a static situation. According to the relative motion theory, the other objects in the video are moving relatively...
Background modeling is one of the most important parts of visual surveillance systems. Most background models are pixel-based which extract detailed shape of moving objects, but they are so sensitive to non-stationary scenes. In many applications there is no need to detect the detailed shape of moving objects. So some researchers use block-based methods instead of pixel-based which are more insensitive...
For a typical urban intersection, moving vehicle shadow and vehicle-pedestrian mixed conditions exist in traffic scene commonly. These interfering factors lead to a very low correct rate of the traffic parameters extraction. This paper presents robust traffic parameters extraction (RTPE) approach for traffic surveillance system at an urban intersection, which contains three key algorithms. First,...
Motion classification is the first step of gait recognition. The classification of motion is conducted, and behavior validity can be made under specific scenarios. In order to identify people movement in an intelligent security monitoring system, moving body is detected and the boundary is extracted. The paper proposes a complex number notation based on centroid in order to indicate a pedestrian's...
This paper discusses a method for abnormal motion detection and its real-time implementation on a smart camera. Abnormal motion detection is a surveillance technique that only allows unfamiliar motion patterns to result in alarms. Our approach has two phases. First, normal motion is detected and the motion paths are trained, building up a model of normal behaviour. Feed-forward neural networks are...
The moving objects are what attract most attention in the video surveillance system, and also the key part for study. Currently, the video surveillance system relies much on the subjective initiative of the observers while having the real-time surveillance. In this study, applying the mixture Gaussian model algorithm, the profile image of the moving objects in the picture got from the video surveillance...
Event detection and recognition is an active and challenging topic recent in computer vision. The technique could be applied in many visual surveillance systems. This paper describes a new method of recognizing events from video sequences in an office environment. The proposed approach is the vision based human motion analysis via motion history image (MHI) sequences and is invariant to body shape,...
This paper proposes a new method for multisensor background extraction and updating aimed at surveillance and target detection applications. The background scene extraction is based on robust multisensor change detection of moving objects in the scene. An iterative mechanism updates the background estimate using this information thereby ignoring transient objects but allowing for slow changes in scene...
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