Analysis of Target Detection and Tracking for Intelligent Vision System

Abstract

In the present scenario, most of the researchers are highly motivated to do new findings in the field of computer vision because of its tremendous applications such as video surveillance, human-machine interaction, traffic monitoring, human behavioral analysis, the guided missile, and military services, medical applications, and vehicle navigation. A typical video data frame comprises both foregrounds as well as background information. The pixel points that describe the target features in the region of interest are considered foreground information, and the rest of the feature points are treated as background information. Moving object detection plays a pivotal role in any kind of computer vision applications. Moving object detection is the process of identifying the class objects such as people, vehicles, toys, and human faces in the video sequences more precisely without background disturbances. In most cases, the existing moving object detection approaches concentrate only on the foreground information and frequently ignore the background information. As a result, trackers will be deviated away from the target and detect the non-foreground objects. Recently, several contributions have been proposed for moving object detection. However, the robustness and novelty are still challenging to achieve because of the complex environments, including illumination changes, rapid variations in target appearance, similar objects in the background, occlusions, target rotations, scaling, fast and abrupt motion changes, moving soft shadow, flat surface regions, and dynamic backgrounds. This book chapter introduces the concept of an intelligent video surveillance system and the major challenges involved in moving object detection. This chapter also deliberates the related backgrounds and their shortcomings in different perspectives. It also presents potential algorithms for efficient object detection and tracking. Finally, the book chapter is concluded with research opportunities pertaining to object detection and tracking.