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IJSDR
INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15

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Volume 9 | Issue 4

Impact factor: 8.15

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Paper Title: IoT Based Smart Object Detector: A Survey
Authors Name: Sharik Sameera Maliksab Mulla , Anjana P. Umarji , Aishwarya B. Sangapur , Saniha Hunur , Parashuram K. Deshpande
Unique Id: IJSDR2303011
Published In: Volume 8 Issue 3, March-2023
Abstract: The survey addresses how an IOT smart device helps Object detection, tracking, and recognition recently have been amongst the most interesting topics for research in computer vision and its application. Object tracking is a computer vision technique used to locate and follow objects of interest in a video stream. The goal of object tracking is to track the movement of the object through the frames of the video, even if the object undergoes changes in size, orientation, or illumination. Object tracking has applications in various fields, including security surveillance, traffic monitoring, sports analysis, and robotics. Object trackers use a variety of techniques, including feature-based tracking, appearance-based tracking, and motion-based tracking. Feature-based tracking involves detecting key features of the object and using them to track its movement. Appearance-based tracking involves creating a model of the object's appearance and using it to identify the object in subsequent frames. Motion-based tracking involves using the object's motion information to track its movement. There are several challenges in object tracking, including occlusion, motion blur, and changes in lighting conditions. To address these challenges, object trackers often use a combination of techniques and algorithms, including filtering, prediction, and data association. Deep learning-based approaches, including convolutional neural networks (CNNs) and recurrent neural networks (RNNs), have also shown promising results in object tracking. This survey may help to track and monitor the objects. In this paper initially the introduction is given, next to it the elaboration of some papers related to the topic are explained and so on followed by the conclusion.
Keywords: Object Tracking, Object Detection, Motion blur, Security surveillance
Cite Article: "IoT Based Smart Object Detector: A Survey", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.8, Issue 3, page no.50 - 57, March-2023, Available :http://www.ijsdr.org/papers/IJSDR2303011.pdf
Downloads: 000337070
Publication Details: Published Paper ID: IJSDR2303011
Registration ID:204278
Published In: Volume 8 Issue 3, March-2023
DOI (Digital Object Identifier):
Page No: 50 - 57
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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