Moving object target detection has a significant interest in image analysis. Frames are extracted from the real-time video, and from this image the required target is detected. This paper presents a contour-based object tracking using the spatial information. The image is applied for multiple segmentations to partition the image into simpler segments. Then automatic identification is done using...

Tracking the real world coordinate of a fast moving object against a complex background is very challenging. When designing a multi-view system for this purpose, one key consideration is the arrangement of the cameras such that the object can be constantly and accurately tracked. This paper discusses a novel cameras arrangement, which can provide redundancy for fault tolerance, yet do not requi...

Title of dissertation: ADAPTIVE KERNEL DENSITY APPROXIMATION AND ITS APPLICATIONS TO REAL-TIME COMPUTER VISION Bohyung Han, Doctor of Philosophy, 2005 Dissertation directed by: Professor Larry S. Davis Department of Computer Science Density-based modeling of visual features is very common in computer vision research due to the uncertainty of observed data; so accurate and simple density represe...

We propose a framework of a multi-object tracking method based on image classification. Aiming to build an appearance model of a target, a sparse measurement matrix is used as a projection for dimensional reduction and online feature selection to improve discriminative power. Our main idea is putting appropriate weights on the features selected to form a feature pattern. Using our method, it is...

Vehicle tracking is important in traffic monitoring systems. The behaviors of regions of moving vehicles are complicated, since the regions may combine or break during the tracking due to mistakes in vehicle detection and tracking or vehicles’ overlapping with each other, and as a result, region matching simply according to similarities between successive frames is not enough to achieve reliabl...

An efficient moving object Segmentation is useful for real time content based video surveillance and Object Tracking. Commonly a foreground is extracted using a mixture of Gaussian followed by shadow and noise removal to initialise the Object Trackers. This technique uses a kernel mask to make the system more efficient by decreasing the search area and the number of iterations to converge in th...

The main objective of this paper is to develop multiple human object tracking approach based on motion estimation and detection, background subtraction, shadow removal and occlusion detection. A reference frame is initially used and considered as background information. While a new object enters into the frame, the foreground information and background information are identified using the refer...

Video tracking is the process of locating a moving object in time that is visualized by camera and are widely used in surveillance, animation and robotics Tracking describes the process of recording movement and translating that movement onto a digital model. The set of constraints that produce the most accurate tracking is the one that describes better the action performed. The key difficulty ...

motion analysis and quality assessment of human sperm cell is of great importance for clinical applications of male infertility. sperm tracking is quite complex due to cell collision, occlusion and missed detection. the goal of this study is simultaneous tracking of multiple human sperm cells. in the first step in this research the frame difference algorithm is used for background subtraction. ...

Object tracking is one of the most challenging task and has secured significant attention of computer vision researchers in the past two decades. Recent deep learning based trackers have shown good performance on various tracking challenges. A tracking method should track objects in sequential frames accurately in challenges such as deformation, low resolution, occlusion, scale and light variat...