Multiple Object Detection and Tracking: A Survey (original) (raw)

SURVEY ON DIFFERENT TECHNIQUES OF OBJECT DETECTION AND TRACKING

This paper describes different methods used for multiple object detection and tracking. Although object recognition have projected many challenges because the algorithms did not give correct results. From time to time, several techniques have been discovered to identify the object. The most important objective is to determine the various methods in static as well as moving object detection and tracking of moving objects. Any video scene containing objects can be determined by means of object detection technique. The detection for moving object is a very challenging task for any video surveillance system. This survey paper proposes a classification of these strategies with detailed discussion on their advantages and disadvantages.

Multiple Object Detection and Tracking

Object detection and tracking is one of the most common and demanding tasks that surveillance systems need to perform in order to detect meaningful events and suspicious activity and automatically comment and retrieve video content. The reason object detection and tracking are grouped is that object detection can be considered the basis of object tracking, and everyone needs to choose the right features and train for effective classification. Object detection and tracking is one of the key areas of research due to routine changes in object movement, scene size changes, occlusions, appearance changes, and lighting changes. This is relevant for many real-time applications such as vehicle perception and video surveillance. Tracking is performed in terms of object movement and appearance to overcome cognitive problems. Object recognition is one of the most basic and central tasks of computer vision. Its task is to find all the objects of interest in the image and determine the categories and positions of the objects. Object recognition is widely used, has high practical value, and has high research prospects. Object Tracking is a deep learning application that takes an initial set of object detections, creates a unique identifier for each initial detection, and tracks the objects detected as they move within a frame in the video. Algorithms used for implementation of above concepts are CNN, RCNN, Yolo and deep sort methods.

IJERT-A Survey : On Multiple Object Detection and Tracking

International Journal of Engineering Research and Technology (IJERT), 2014

https://www.ijert.org/a-survey-on-multiple-object-detection-and-tracking https://www.ijert.org/research/a-survey-on-multiple-object-detection-and-tracking-IJERTV3IS10574.pdf Object tracking is an important task in the field of computer vision. It is a challenging problem. There are many difficulties arises in tracking the objects due to abrupt object motion, changing appearance patterns of both foreground and background scene, non-rigid object structures, object-to-object and object-to-scene occlusions, and camera motion. This paper selectively gives the reviews to research papers for object detection and tracking methods.

Techniques for Detection and Tracking of Multiple Objects

2017

During the past decade, object detection and object tracking in videos have received a great deal of attention from the research community in view of their many applications, such as human activity recognition, human computer interaction, crowd scene analysis, video surveillance, sports video analysis, autonomous vehicle navigation, driver assistance systems, and traffic management. Object detection and object tracking face a number of challenges such as variation in scale, appearance, view of the objects, as well as occlusion, and changes in illumination and environmental conditions. Object tracking has some other challenges such as similar appearance among multiple targets and long-term occlusion, which may cause failure in tracking. Detection-based tracking techniques use an object detector for guiding the tracking process. However, existing object detectors usually suffer from detection errors, which may mislead the trackers, if used for tracking. Thus, improving the performance...

A Review on Object Detection and Tracking in Video

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.

A Survey on Object Detection and Tracking Methods

International Journal of Innovative Research in Computer and Communication Engineering, 2014

The goal of object tracking is segmenting a region of interest from a video scene and keeping track of its motion, positioning and occlusion.The object detection and object classification are preceding steps for tracking an object in sequence of images. Object detection is performed to check existence of objects in video and to precisely locate that object. Then detected object can be classified in various categories such as humans, vehicles, birds, floating clouds, swaying tree and other moving objects. Object tracking is performed using monitoring objects’ spatial and temporal changes during a video sequence, including its presence, position, size, shape, etc.Object tracking is used in several applications such as video surveillance, robot vision, traffic monitoring, Video inpainting and Animation. This paper presents a brief survey of different object detection, object classification and object tracking algorithms available in the literature including analysis and comparative stu...

Detection and Tracking of Objects: A Detailed Study

Detecting and tracking objects are the most widespread and challenging tasks that a surveillance system must achieve to determine expressive events and activities, and automatically interpret and recover video content. An object can be a queue of people, a human, a head or a face. The goal of this article is to state the Detecting and tracking methods, classify them into different categories, and identify new trends, we introduce main trends and provide method to give a perception to fundamental ideas as well as to show their limitations in the object detection and tracking for more effective video analytics.

Different Techniques of Object Detection and Tracking: In Video Monitoring System

2020

The paper includes the various methods which are related to object detection and tracking in live video surveillance to detect the object like the face or can be used to detect the people, cars in a security camera. These days we can easily find that people are following social distancing due to COVID -19. This paper point towards the various methods of detecting the object (classification) and tracking (GMM tracking). This paper points toward the detection of movable objects in the live video monitoring then tracking will track the moving object. Detecting a moving object is really a very big task and it the origin of the method. Object detection is really difficult to implement which depends upon the shape size and color of the object. In this paper, we will study the background subtraction using the pixel-based method, optical flow method, color-based method gradient-based method and frame differencing. We will also study tracking methods like kernel-based method silhouette-based...

Overview Of Video Object Tracking System

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.