Video Tracking provides a comprehensive treatment of the fundamental aspects of algorithm and application development for the task of estimating, over time, the position of objects of interest seen through cameras. Starting from the general problem definition and a review of existing and emerging video tracking applications, the book discusses popular methods, such as those based on correlation and gradient-descent. Using practical examples, the reader is introduced to the advantages and limitations of deterministic approaches, and is then guided toward more advanced video tracking solutions, such as those based on the Bayes’ recursive framework and on Random Finite Sets. Key features: Discusses the design choices and implementation issues required to turn the underlying mathematical models into a real-world effective tracking systems. Provides block diagrams and simil-code implementation of the algorithms. Reviews methods to evaluate the performance of video trackers – this is identified as a major problem by end-users. The book aims to help researchers and practitioners develop techniques and solutions based on the potential of video tracking applications. The design methodologies discussed throughout the book provide guidelines for developers in the industry working on vision-based applications. The book may also serve as a reference for engineering and computer science graduate students involved in vision, robotics, human-computer interaction, smart environments and virtual reality programmes

The research on computer vision systems has been increasing every day and has led to the design of multiple types of these systems with innumerous applications in our daily life. The recent advances in artificial intelligence, together with the huge amount of digital visual data now available, have boosted vision system performance in several ways. Information extraction and visual object tracking are essential tasks in the field of computer vision with a huge number of real-world applications.This book is a result of research done by several researchers and professionals who have highly contributed to the field of image processing. It contains eight chapters divided into three sections. Section 1 consists of four chapters focusing on the problem of visual tracking. Section 2 includes three chapters focusing on information extraction from images. Finally, Section 3 includes one chapter that presents new advances in image sensors.

Object tracking could be a terribly difficult task within the presence of variability illumination condition, background motion, complicated object form, partial and full object occlusions. The main intention of an object trailer is to make the path of an object over time by characteristic its position in all frames of the video. This book is intended to educate the researchers in the field of tracking of moving object(s) in a video sequence. This book provides a path for the researchers to identify the works done by others in the same field and thereby to figure out the gap in the current knowledge. This book is organized into three Modules. Module 1 talks about the introduction of object detection and tracking. Module 2 discusses about the various studies of object tracking and motion detection. The views of the various authors about this hot research topic are discussed in this Module and Module 3 gives the conclusion of the entire research review.Object tracking could be a terribly difficult task within the presence of variability illumination condition, background motion, complicated object form, partial and full object occlusions. The main intention of an object trailer is to make the path of an object over time by characteristic its position in all frames of the video. This book is intended to educate the researchers in the field of tracking of moving object(s) in a video sequence. This book provides a path for the researchers to identify the works done by others in the same field and thereby to figure out the gap in the current knowledge. This book is organized into three Modules. Module 1 talks about the introduction of object detection and tracking. Module 2 discusses about the various studies of object tracking and motion detection. The views of the various authors about this hot research topic are discussed in this Module and Module 3 gives the conclusion of the entire research review.

Computer vision systems attempt to understand a scene and its components from mostly visual information. The geometry exhibited by the real world, the influence of material properties on scattering of incident light, and the process of imaging introduce constraints and properties that are key to solving some of these tasks. In the presence of noisy observations and other uncertainties, the algorithms make use of statistical methods for robust inference. In this paper, we highlight the role of geometric constraints in statistical estimation methods, and how the interplay of geometry and statistics leads to the choice and design of algorithms. In particular, we illustrate the role of imaging, illumination, and motion constraints in classical vision problems such as tracking, structure from motion, metrology, activity analysis and recognition, and appropriate statistical methods used in each of these problems.

This work proposes a feature-based probabilistic data association and tracking approach (FBPDATA) for multi-object tracking. FBPDATA is based on re-identification and tracking of individual video image points (feature points) and aims at solving the problems of partial, split (fragmented), bloated or missed detections, which are due to sensory or algorithmic restrictions, limited field of view of the sensors, as well as occlusion situations.

In digital marketing, your goal is to funnel your potential customers from the point of making them aware of your website, through engagement and conversion, and ultimately retaining them as loyal customers. Your strategies must be based on careful analysis so you know what is working for you at each stage. Adobe Analytics with SiteCatalyst Classroom in a Book teaches effective techniques for using Adobe SiteCatalyst to establish and measure key performance indicators (KPIs) tailored to your business and website. For each phase of marketing funnel analytics, author Vidya Subramanian walks you through multiple reports, showing you how to interpret the data and highlighting implementation details that affect data quality. With this essential guide, you'll learn to optimize your web analytics results with SiteCatalyst. Adobe Analytics with SiteCatalyst Classroom in a Book contains 10 lessons. The book covers the basics of learning Adobe SiteCatalyst and provides countless tips and techniques to help you become more productive with the program. You can follow the book from start to finish or choose only those lessons that interest you. Classroom in a Book®, the best-selling series of hands-on software training workbooks, helps you learn the features of Adobe software quickly and easily. Classroom in a Book offers what no other book or training program does—an official training series from Adobe Systems Incorporated, developed with the support of Adobe product experts.