A Survey on Moving Object Detection and Tracking Methods

-The researchers has attracted on object tracking research. There are many tracking algorithm, The purpose of object tracking algorithm is segmenting a region of interest from a video scene and keeping track of its motion, positioning and occlusion. Preceding steps for tracking an object in sequence of images are the object detection and object classification. To check existence and to locate that objects in video, Object detection is performed. The detected object can be classified among the various categories such as humans, vehicles, birds, floating clouds, swaying tree and other moving objects. Object tracking is performed by monitoring objects’ spatial and temporal changes like its presence, position, size, shape, etc. during a video sequence. This paper presents a brief survey of different object detection, object classification and object tracking algorithms available in the literature including analysis and comparative study of different techniques which one used for various stages of tracking. Keywords--Object Detection, Object Tracking, Background Subtraction, Gaussian Mixture Model, Optical Flow I. INT RODUCTION Many researchers are attracted to research on moving Object detection and tracking. In the domain of computer vision, object tracking plays a very important role. Actually sequences of images are called videos, each of which called a frame. Frame can be displayed in fast enough frequency so that human eyes can percept the continuity of its content. All image processing techniques applied on each frame and also content of two consecutive frames are closely related [3]. From a video sequence, an image is divided into two complimentary sets of pixels, in which he first set contains the pixels which correspond to foreground objects which is usually moving objects like people, boats and cars and everything else is background while the second complimentary set contains the background pixels. This result is often represented as a binary image or as a mask [4]. Many a time’s shadow is represented as foreground object which gives improper output. Object tracking has significance in the real time environment because it enables several important applications such as Security & Surveillance to recognize people as well to provide better sense of security using visual information, In Medical therapy it improves the quality of life for physical therapy patients and disabled, In Retail space instrumentation to analyses shopping behavior of customers to enhance building and environment design, Video abstraction which used to obtain automatic annotation of videos which generate object based summaries, Traffic management to analyses flow and detect accidents, Video editing for eliminate cumbersome human operator interaction, to design futuristic video effects. The detection of moving objects is the foundation of other advanced applications, such as target tracking, targets classification and target behavior understanding [2]. The basic steps for tracking an object are described below: Fig 1: Basic steps for detection and tracking of an object II. OBJ ECT DET ECT ION M ET HODS: The Object detection and tracking are playing an important role in many pattern recognition and computer vision pattern recognition applications like autonomous robot navigation, surveillance and vehicle navigation. An object detection mechanism used in when the object first appears or in every frame in the video. In order to reduce the number of false detection and increase accuracy rate [1], some object detection methods use the temporal information computed from analyzing a sequence of frames. Object detection can be done by various techniques such as temporal differencing [9], frame differencing [7], Optical flow [4] and Background subtraction [6, 8]. A. Frame differencing: The existence of moving objects is determined by calculating the difference between two consecutive images. Frame differencing technique is very simple and also easy to define but it is generally difficult to achieve complete summary of moving object as a result of the detection of moving object is not accurate [7]. VIDEO SEQUENCE