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This paper reports the development of a reliable vision-based eye-gaze detection system for an analysis of multiple users' intention and communication. Headgear design for the gaze detection, a recording system, an off-line computation, an algorithm of the gaze extraction, and its calibration method, are mentioned. Applying the proposed system to a test case, sufficient precision of the gaze detection...
This paper describes a technique for recovering 3-D shape of a non rigid object employing a single camera. 3-D modeling of a non-rigid object has been studied employing multiple cameras. However it can be realized even by a single camera on condition that the object concerned is composed of a set of rigid objects. Experimental results show effectiveness of the proposed technique.
In networked virtual environments, videoconferences or chatting over the Internet users are often graphically represented by virtual characters. Modeling realistic virtual heads of users suitable for animation implies a heavy artistic effort and resource cost. This paper introduces a system that generates a 3D model of a real human head with a little human intervention. The system receives five input...
This paper introduces a non-temporal multiple silhouettes in Hidden Markov Model (HMM) for offering view independent human posture recognition. The multiple silhouettes are used to reduce the ambiguity problem of posture recognition. A simple feature extraction of the 2D shape contour based histogram is used for image encoding and K-Means algorithm is applied for clustering and code-wording of eight...
In this paper, we present a novel person detection system for public transport buses tackling the problem of changing illumination conditions. Our approach integrates a stable SIFT (scale invariant feature transform) background seat modeling mechanism with a human shape model into a weighted Bayesian framework to detect passengers on-board buses. SIFT background modeling extracts local stable features...
To address the challenges on non-cooperative long-distance human identification and verification, we propose an innovative cost-efficient system for automatic long-range biometric recognition of non-cooperative individuals in 24/7 operations. The system has three cameras. One is a wide field of view (WFOV) CCD video camera with an Infrared (IR) filter and powerful IR illuminators for human scan in...
Most existing algorithms for human behavior analysis concentrate on action recognition through assuming that input sequences are well pre-segmented and restricting examples into a small vocabulary. In this paper, we present a novel action violence classification framework which directly evaluates the potential threat based on shape variations. We extract silhouettes as input features, employ the R...
In this paper, we investigate the efficiency of different view angles when classifying gender with gait biometrics for the first time. A gait database is built for this purpose in which walking videos are recorded at seven different views for each subject. Then, we employ a robust gait representation method to extract gait features. The class separability of these features from different view angles...
This paper presents a method for monitoring activities at a ticket vending machine in a video-surveillance context. Rather than relying on the output of a tracking module, which is prone to errors, the events are directly recognized from image measurements. This especially does not require tracking. A statistical layered approach is proposed, where in the first layer, several sub-events are defined...
Local invariant feature based methods have been proven to be effective in computer vision for object recognition and learning. But for an image, the number of points detected and to be matched may be very large, or even redundantly represent the shape information present. Since selective attention is a basic mechanism of the visual system, we explore whether there is a subset of salient points that...
Video surveillance is an omnipresent topic when it comes to enhancing security and safety in the intelligent home environments. In this paper, we propose a novel method to detect various posture-based events in a typical elderly monitoring application in a home surveillance scenario. These events include normal daily life activities, abnormal behaviors and unusual events. Due to the fact that falling...
Fall detection system for intelligent home care for elderly people is presented in this paper. The system includes human blob detection by non-parameter background substruction method, feature extraction from two minimum bounding boxes, and fall detection by a cascaded multi-SVM classifier. Besides falling down, other daily activities such as walk, jogging, sitting down, squatting down and immobility...
During last years, robotic research has explored Human-Robot interactions especially for the challenge of the robot companion. This type of robot would be equipped with perception, motion, and manipulation among other skills, to be help humans in daily tasks. Guidance is one of the tasks that the robot companion must perform. This paper describes Robbie, a wheeled robot companion uses for guiding...
In this paper we propose a method for estimating human skeleton proportions automatically from two-dimensional (2D) joint locations extracted from a monocular video. Unlike many other methods where the three-dimensional (3D) human postures are pre-known or posture estimations are required, the proposed method does not require correct posture recoveries for the purpose of acquiring the human skeleton...
This paper suggests a new portable posture input system which consists of a stereo vision system, a color marked puppet, and a laptop computer. Using the puppet, we can intuitively input any posture which we want to represent. The puppet posture is recognized by the stereo vision. First, the color mark of each puppet joint is obtained and segmented. In this case, the normalized color technique is...
Differentiating between normal human activity and aberrant behavior via closed circuit television cameras is a difficult and fatiguing task. The vigilance required of human observers when engaged in such tasks must remain constant, yet attention falls off dramatically over time. In this paper we propose an architecture for capturing data and creating a test and evaluation system to monitor video sensors...
We propose a new method for human action recognition from video streams that is fast and robust to noise and to large changes in camera views. We start by extracting features in the Fourier domain once we obtain the bounding boxes containing the silhouettes of a human for a number of video frames representing a basic action. After preprocessing, we divide each space-time volume into space-time sub-volumes...
This paper describes a technique for extracting moving objects from a video image sequence taken by a fixed or slowly moving camera by background subtraction. The background subtraction method is effective for extracting moving objects from a video provided by a fixed camera. But the latest background image should be employed for the subtraction in order not to be influenced by the light intensity...
Surveillance cameras are inexpensive and everywhere these days but the manpower required to monitor and analyze them is expensive. Consequently the videos from these cameras are usually monitored sparingly or not at all; they are often used merely as archive, to refer back to once an incident is known to have taken place. Surveillance cameras can be a far more useful tool if instead of passively recording...
Multiple object association is an important capability in visual surveillance system with multiple cameras. An association approach using the limits of field of View (FOV) of cameras is well accepted but this approach has to wait until the object crosses the limits for association. Also, FOV information has to be determined whenever the setup of camera is changed. Our approach is to dynamically generate...
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