Object tracking system based on invariant features

Mahendran, Siddharth; Vaithiyanathan, D.; Seshasayanan, R.

doi:10.1109/iccsp.2013.6577234

Cited by 12 publications

(3 citation statements)

References 7 publications

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“…In the training phase, separating the modelled static background frame using Gaussian mixture models (GMM) for blob detection and this will be carried out for every frame for tracking purpose. In April 2013, [4] presented a paper we propose the use of Distance Metric Learning (DML) in combination with Nearest Neighbour (NN) classification for object tracking. Initially a video file is read and the frames in the video are accessed individually.…”

Section: Literature Surveymentioning

confidence: 99%

Tracking Human Motion Based on Bounding Box Concept

Lande¹

2018

IJRASET

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This paper presents moving object detection based on background subtraction for video surveillance system. In all computer vision system, the important step is to separate moving object from background and thus detecting all the objects from video images. The main aim of this paper is to design a bounding box concept and alarm system for the human detection and tracking system in the presence of crowd. The bounding box around each object can track the moving objects in each frame and alarm will fire when object is detected and it can be used to detect crowd or theft and the estimation of crowd. This paper gives the implementation results of bounding box and alarm system for detecting objects and its tracking. The evaluation test performed on proposed system like PSNR, MSE was found.

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Section: Literature Surveymentioning

confidence: 99%

Tracking Human Motion Based on Bounding Box Concept

Lande¹

2018

IJRASET

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“…Most of the computer vision systems struggle to recognize human action in more complex scenes such as street monitoring but has its own constraints in system design such as object detection is not accurate due to lighting variation in the environment and the people detection is very difficult in human crowded image [4]. The people activity monitoring may be much harder in the presence of occlusion and crowd.…”

Section: Introductionmentioning

confidence: 99%

Human recognition for surveillance systems using bounding box

Deepak

Krishnakumar

Suresh³

2014

2014 International Conference on Contemporary Computing and Informatics (IC3I)

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In all computer vision system, the important step is to separate moving object from background and thus detecting all the objects from video images. The main aim of this paper is to design a bounding box concept for the human detection and tracking system in the presence of crowd. The images are captured by using monocular cameras. The bounding box around each object can track the moving objects in each frame and it can be used to detect crowd and the estimation of crowd. This paper gives the implementation results of bounding box for detecting objects and its tracking.

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“…Now a day tracking an target object become the new area of interest in the video surveillance system which become a high priority as presently each organization or building is under CCTV surveillance [1][2]. The basic steps of object tracking are feature extraction, target object representation, searching the target object in the candidate region.…”

Section: Introductionmentioning

confidence: 99%