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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...
This paper presents an efficient real-time implementation of an unsupervised textile fabric defect detection algorithm called ITT using the concept of iterative tensor tracking on graphics processing unit (GPU). The algorithm adopts a new local image descriptor, Spatial Histograms of Oriented Gradients (S-HOG), which is shift-invariant, light insensitive and space scalable. For a given textile fabric...
In this paper we present a system for mobile augmented reality (AR) based on visual recognition. We split the tasks of recognizing an object and tracking it on the user's screen into a server-side and a client-side task, respectively. The capabilities of this hybrid client-server approach are demonstrated with a prototype application on the Android platform, which is able to augment both stationary...
We proposed a tracking and location method for UAVs' Vision System. In our method, the target is extracted from the ROI (Region of Interested) automatically by an analysis of intensity value distribution; then the mean-shift tracker is used to get the target's position in the sequence images; The relative position of the target to the vision system in the real world is reconstructed just by monocular...
This paper presents a completely automated 3D facial feature tracking system using 2D+3D image sequences recorded by a real-time 3D sensor. It is based on local feature detectors constrained by a 3D shape model, using techniques that make it robust under pose and partial occlusion. Several experiments conducted under relatively non-controlled conditions demonstrate the accuracy and robustness of the...
This paper presents a method for rectifying video sequences from rolling shutter (RS) cameras. In contrast to previous RS rectification attempts we model distortions as being caused by the 3D motion of the camera. The camera motion is parametrised as a continuous curve, with knots at the last row of each frame. Curve parameters are solved for using non-linear least squares over inter-frame correspondences...
We derive a probabilistic framework for robust, realtime, visual tracking of multiple previously unseen objects from a moving camera. This framework models the discrete depth ordering of the objects being tracked in the scene. The method uses the observed image data to compute a posterior over the objects' poses, shapes and relative depths. The poses are group transformations, the shapes are implicit...
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