Today, the market of public surveillance solutions has a huge niche for a computer vision technologies and their implementations. Using these technologies allows us to make a significant step in process automation and data processing, gain meaningful insights from raw data, and improve decision-making. Even though there are some competitors that offer out-of-the box solutions, Oxagile explored one of the most challenging fields of public surveillance domain — tracking live video objects with a moving camera. The task is challenging due to the following factors:. A major task of a typical video object tracking is aimed at keeping track of a chosen object until the very end of video or up to the moment the object disappears. The process starts with a bounding box around an object that is given as a set of coordinates.
Moving Object Recognition and Detection Using Background Subtraction
Moving Object Detection Approaches, Challenges and Object Tracking | SpringerLink
Video tracking is the process of locating a moving object or multiple objects over time using a camera. It has a variety of uses, some of which are: human-computer interaction, security and surveillance, video communication and compression , augmented reality , traffic control, medical imaging  and video editing. Adding further to the complexity is the possible need to use object recognition techniques for tracking, a challenging problem in its own right. The objective of video tracking is to associate target objects in consecutive video frames. The association can be especially difficult when the objects are moving fast relative to the frame rate.
Kalman Filter for Moving Object Tracking: Performance Analysis and Filter Design
To browse Academia. Skip to main content. Log In Sign Up. Download Free DOC. Download Free PDF.
There are various approaches to moving object detection from video; e. This chapter summarizes these methodologies. Different challenging conditions that pose problems in moving object detection are also identified.