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Artificial vision provides a remarkable good sensor when developing applications for intelligent spaces. Cameras are passive sensors that supply a great amount of information and are quite cheap. This paper presents an application for elderly care that detects falls or faints and automatically triggers the health alarm. It promotes the independent lifestyle of elder people at their homes as the monitoring...
Fast algorithms and heuristics for real-time object recognition and tracking have enabled a new hybrid world technology in which one can manipulate a real world object and have its virtual world counterpart move correspondingly. This technology has been developed as part of a teaching head platform that was initially designed for language teaching but is now also being used in a range of health-oriented...
The traditional mean shift tracking method can not acquire high accuracy when the object undergoes partial occlusion. An improved tracking method called mean shift rectification is proposed. The candidate matching points in target region searched by mean shift method are filtered using a log-likelihood ratio function, and the target region is divided into subregions. Then the spatial matching restrictions...
As long as visual features for recognition are known in advance and remain static due to a controlled environment, object tracking is state-of-the-art. Tracking objects in dynamically changing environments is still a challenge. Even harder is the tracking of moving objects with a moving camera. Our algorithm realizes a deterministic approach to track any 2D-features representable in a general way...
In this paper we present an effective real-time video surveillance system for real-life outdoor surveillance scenarios. The system is an integration of two subsystems: the static camera and moving one. The approaches employed address properly the challenges that might arise in a typical outdoor scene, such as local and global lighting changes, variations in objects' appearance and occlusions. Our...
Autonomous video surveillance and monitoring has a rich history. A new method for detecting and tracking multiple moving objects based on discrete wavelet transform and identifying the moving objects by their color and spatial information is proposed in this paper. Since discrete wavelet transform has a nice property that it can divide a frame into four different frequency bands without loss of the...
Making the use of the characteristics of accuracy using normalized cross-correlation image matching, this paper introduces normalized cross-correlation into the video processing, and proposes a moving object tracking method based on prediction-based Cross-correlation. First, we get the background of the video using adaptive on-line clustering method, and then get the foreground object of the video...
Correlation based stereo vision has proven its power in commercially available driver assistance systems. Recently, real-time dense stereo vision has become available on inexpensive FPGA hardware. In order to manage the huge amount of data, a medium-level representation named “Stixel World” has been proposed for further analysis. In this representation the free space in front of the vehicle is limited...
In this paper, we propose a vehicle detection and tracking algorithm. The detection is done using the median filtering and blob extraction. Median filtering is used for background extraction which is later subtracted from the motion frames for object detection. Morphological operators are employed for blob extraction. Hence, object detection is achieved using median filtering and morphological closing...
The virtual mouse is an important research topic in HCI (Human Computer Interaction) technology, and the most popular method is based on hand gestures. In this paper, a six-degree-of-freedom virtual mouse based on hand gestures is presented using an inexpensive USB webcam. The hand tracking and gesture recognition framework includes the motion, skin color and finger information of the hand. It can...
Camera networks are important in a video surveillance system. Many surveillance systems research has been done; most of it utilizes a general purpose computer. However, the latest trend is to use small, task specific and low power computer to process and control the system; in another word using embedded systems. This paper presents a camera network localization algorithm to be implemented on a FPGA...
Recently, the studies of human motion analysis have attracted great attention among the researches in the field of biomechanics, medicine and sports by analyzing the joints, postures, and movements of the human. Our research focuses on analyzing the joints movement of a professional golfer. We represent those joint movements with an articulate stick human model. This paper presents a method for tracking...
We propose a system that can reliably track multiple cars in congested traffic environments. Our system's key basis is the implementation of a sequential Monte Carlo algorithm, which introduces robustness against problems arising due to the proximity between vehicles. By directly modelling occlusions and collisions between cars we obtain promising results on an urban traffic dataset. Extensions to...
Visual tracking using Mean Shift is famous and popular. But the traditional Mean Shift tracking algorithm cannot track an object which changes its scale and orientation during the process of tracking. A novel tracking algorithm based on Mean Shift and on-line feature selection is proposed in this paper. Target object is defined in a 4-D state space which can deal with its positon, scale and orientation...
Lane detection and tracking is still a challenging task. Here, we combine the recently introduced Statistical Hough transform (SHT) with a Particle Filter (PF) and show its application for robust lane tracking. SHT improves the standard Hough transform (HT) which was shown to work well for lane detection. We use the local descriptors of the SHT as measurement for the PF, and show how a new three kernel...
A novel strategy of simultaneously tracking and segmentation is proposed for human respiratory rate estimation from thermal infrared, which can be applicable to contact-free polygraphy, airport health screening and patient monitoring system. In this framework, by carefully selecting the adaptive observation model for the tracking template and taking the intensity variation pattern of breathing into...
Natural human-robot interaction requires leveraging viewing direction information in order to recognize, respond to, and even emulate human behavior. Knowledge of the eye gaze and point of regard gives us insight into what the subject is interested in and/or who the subject is addressing. In this paper, we present a novel eye gaze estimation approach for point-of-regard (PoG) tracking. To allow for...
In this paper, we describe a real-time vision-based tracking system to help students who are blind or visually impaired (SBVI) to follow instructional discourse that employs graphical illustrations. The vision system employs a color model based tracking for both the instructor's pointing behavior and the SBVI's reading behavior, and maps the pointing positions into the same coordinates. Our Haptic...
A novel mid-level video indexing method based on detection and tracking human faces is presented. Instead of detecting the faces on every frame, our method first detects the faces and then tracks them. Compared to our previous general-purpose tracking method, our approach is improved by: i) a Multi-Object model extension to track several objects in parallel; ii) a Dual Consistency Check by Kolmogrov-Smirnov...
We propose a principled framework to model persistent motion in dynamic scenes. In contrast to previous efforts on object tracking and optical flow estimation that focus on local motion, we primarily aim at inferring a global model of persistent and collective dynamics. With this in mind, we first introduce the concept of geometric flow that describes motion simultaneously over space and time, and...
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