Abstract
With an increasing demands of video tracking systems with object detection over wide ranges of computer vision applications, it is necessary to understand the strengths and weaknesses of the present situation of approaches. However, there are various publications on different techniques in the visual tracking system associated with video surveillance application. It has been seen that there are prime classes of approaches that are only three, viz. point-based tracking, kernel-based tracking, and silhouette-based tracking. Therefore, this paper contributes to studying the literature published in the last decade to highlight the techniques obtained and brief the tracking performance yields. The paper also highlights the present research trend towards these three core approaches and significantly highlights the open-end research issues in these regards. The prime aim of this paper is to study all the prominent approaches of video tracking system which has been evolved till date in various literatures. The idea is to understand the strength and weakness associated with the standard approach so that new approaches could be effectively act as a guideline for constructing a new upcoming model. The prominent challenge in reviewing the existing approaches are that all the approaches are targeted towards achieving accuracy, whereas there are various other connected problems with internal process which has not been considered for e.g. feature extraction, processing time, dimensional problems, non-inclusion of contextual factor, which has been an outcome of the proposed review findings. The paper concluded by highlighting this as research gap acting as contribution of this review work and further states that there are some good possibilities of new work evolution if these issues are considered prior to developing any video tracking system. Overall, this paper offers an unbiased picture of the current state of video tracking approaches to be considered for developing any upcoming model.
Highlights
With the advancement of computer vision and video surveillance systems, video tracking has gained immense popularity in both domestic and commercial applications [1]
Apart from its applicability towards video surveillance systems, video tracking is used over various applications: viz. video editing, medical imaging, traffic control, augmented reality, communication, and video compression, human and computer communication [3,4,5]
Apart from this, the number of journal publications towards kernel-based is significantly less as compared to pointbased tracking. This eventually shows that there was no equal emphasis being given to all the taxonomies of the video tracking system
Summary
With the advancement of computer vision and video surveillance systems, video tracking has gained immense popularity in both domestic and commercial applications [1]. The video tracking system aims to connect the mobile target object (or multiple objects) present over a sequence of video frames. In order to address this conventional issue, the motion model is adopted in the video tracking system [8] This motion model is responsible for defining the relationship between the target object image and its influence over the mobility scenario. The second kind of algorithm mainly deals with the dynamics of the target object and performs assessment based on multiple hypotheses Thereby, such an algorithm results in enhance capability towards tracking mobile objects of complex form. There are consistent evolution of various approaches in order to assist in internal processing of video frames in image processing This leads to a motivating factor that this topic is worth doing a research on owing to its abundant scope of application in upcoming days as well as trade-off in finding any potential standardized model
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