A review on real time object tracking in video sequences

International Journal of Scientific Research in Science, Engineering and Technology, 2019

In video or an image, object detection and tracking is most popular now a days and use for motion detection of various object. Identify objects in the video sequence and cluster pixels of these object is the first step in object detection. Object classification is the next important step to track the object. The object tracking can be applied in most of the fields that include computerized video surveillance, robotic vision, traffic monitoring, gesture identification, human-computer interaction, military surveillance system, vehicle navigation, medical imaging, biomedical image analysis and many more. The objective of this paper is to present the various steps included in tracking objects in a video sequence, namely object detection, object classification and object tracking. This paper presents various object detection and tracking methods and also the comparison of various techniques used for different stages of tracking.

Real time moving object detection and tracking is one of the important research fields that have gained a lot of attention in the last few years. Tracking is required for security, safety and site management. Cameras installed around us but there are no means to monitor all of them continuously. It is necessary to develop technologies that automatically process those images in order to detect problematic situations or unusual behavior of human or object. Design computer vision base automated video surveillance system addresses real-time observation of object within a busy environment leading to the description of their actions and interactions. Object detection by background subtraction technique. Using single camera we detect and track human behavior. Background subtraction is the process of separating out the foreground objects from the background in a sequence of video frames. If human entity is cross the line design security in mall or public area the object is tracked. It is laborious to track and trace people over multiple cameras. In this paper, we present review for some system for real-time tracking and fast interactive retrieval of persons in video streams from single static surveillance camera.

2014

The goal of video object tracking system is segmenting a region of interest from a video scene and keeping track of its motion, positioning and occlusion. There are the three steps of video object tracking system those are object detection, object classification and object tracking. Object detection is performed to check existence of objects in video. Then the detected object can be classified in various categories on the basis on their shape, motion, color and texture. Object tracking is performed using monitoring object changes. This paper we are going to take overview of different object detection, object classification and object tracking techniques and also the comparison of different techniques used for various stages of tracking.

International Journal of Computer Applications, 2017

Computer Vision (CV) concentrates on the automatic extraction, examination and comprehension of valuable data from a solitary image or a group of images. Object tracking, one of the key areas in CV has received a lot of attenstion in recent times. Tracking objects is a systematic process of monitoring the movement of a target object from its initial state to the nth state over a period of time using a camera. This technique is usually employed as a security feature in both military and civilian systems. However, prior studies has shown that tracking objects in motion is a very difficult task and is a hot research hotspot in the field of computer vision and machine learning. In this review paper we discuess various techniques in detection, tracking and some other related works of moving objects in video streams.

International Journal of Innovative Computer Science & Engineering, 2015

This Paper explores the detection and tracking of single real time moving object from the sequence of the frame and also to extract, recognize, and tracking an object without changing its perspective, position, radiance and any deformity The central objective of thesis is to examine the difficulties carry out for classification of object detection and tracking methods.This paper defines the existence of moving object in the video frames and to keep the track of an object's motion and positioning. This paper basically defines an explanation of different object detection and tracking process method using different algorithms. Thus, this object detection and tracking carried into two steps such as frame subtraction using OTSU's thresholding technique. Object representation using point which is a centroid. Kalman filter for object tracking. The work motivated in this paper for relevant extraction of an object from its foreground and background interference using different subtraction and filtering methods. Where first step will be the object detection using frame subtraction method and tracking can be done using kalman filter. These steps will help in object detection and tracking.

In this survey paper we present an approach to define the existence of moving object in the video frames and to keep the track of an object’s motion and positioning. A static camera is used to grab the video. Video is actually sequence of images which are known as frames. We can identify the object using different algorithms and tracking can be defined by using different filters. Object detection and tracking can be classified using different properties of that object like color, size, texture, optical flow, edges position, shape, distance etc. Detected object can be of various categories such as humans, vehicles, birds, moving ball and other moving objects. Object tracking is used in several applications such as video surveillance, person identification, robot vision, behavior analysis, security, traffic monitoring, image retrieval, face detection, animation etc. This survey paper basically defines a brief survey of different object detection and tracking techniques using different algorithms.

This paper presents survey on moving object detection and tracking methods is presented by classifying them into different categories and identify new trends. This survey shows moving object detection and tracking using different and efficient methodologies. Object detection and object tracking is used to track the object type(such as human, vehicles) and detect the movement of the object(such as moving, standing).This survey shows various methodologies for object detection and tracking such as background subtraction, background modeling, intensity range based background subtraction. The simulated result shows that used methodologies for effective object detection has better accuracy and with less processing time consumption rather than existing methods.

2016

Detecting and tracking objects in crowded areas is a challenging issue in the field of Video Surveillance System. Nowadays the increase of digital video cameras, and the availability of video storage and high performance video processing hardware, opens up conceivable outcomes for tackling many video understanding problems. Developing a real-time video understanding technique which can process the large amounts of data becomes very important. The object detection first step used in surveillance applications aims to separation of foreground objects from the background. Many algorithms proposed to solve the problem of object detection, however, it still lack of tracking multiple objects in real time. Object tracking used to find a moving object detected in motion detection stage from one frame to another in an image sequence. This paper focuses on review of various techniques used in object detection and object tracking.

TJPRC, 2013

Now a day, video surveillance is a part of our day to day life. In every private institute, company, government hospitals, offices, school, colleges, everywhere we need object tracking system for security purpose. Visual monitoring of activities using cameras automatically without human intervention is a challenging problem. Moving object detection is very important in intelligent surveillance. In this paper, an improved algorithm based on frame difference is presented for moving object detection. The method of motion detection and tracking is background subtraction. This paper presents a new object tracking model that systematically combines region and shape features. We design a new object detector for accurate and robust tracking in low-contrast, in noisy environment and complex scenes, which usually appear in the commonly used surveillance systems.

OBJECTS TRACKING IN A VIDEO SEQUENCE. This paper presents the result of implementing a tracking system for identifying objects in a video sequence. The main objective of this research is to keep track of objects movement and their activities which are then analyzed whether the activities related to suspicious activities or not. At this stage the research is concentrated on the keep track of the objects once the objects enter the scene. The objects tracking are done by identify objects' movement from video sequence using frame by frame analysis. In order to avoid tracking unnecessary objects a method is implemented to eliminate such objects. In this research a method to eliminate such objects is to use spatial objects information. Based on the described method the research shows that objects tracking in a video sequence can be implemented. Moreover, the research is also trying to isolate objects so that the object size and its activities can be analyzed. Finally, this research h...