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2021 | OriginalPaper | Chapter

A Review of Anomaly Detection Techniques Using Computer Vision

Authors : Vandana Mohindru, Shafali Singla

Published in: Recent Innovations in Computing

Publisher: Springer Singapore

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Abstract

Obtaining videos for surveillance purpose or to use them for future predictions is a challenging task as a video has a large number of image frames displayed in a sequence, and modeling every frame is not possible, so various methods are used for building an intelligent vision system, which is used for obtaining videos and also in video anomaly detection. This paper provides an overview of research directions for different types of anomalies and also tells about different techniques in machine learning for managing the problem of anomaly detection in videos and images using computer vision. Computer vision is used to make computers capable of extracting information from digital images or videos. It trains computers to interpret and understand the visual world. When machines detect errors, abnormal or unnatural behavior of datasets, it is called anomaly detection. In this paper, anomaly detection techniques and anomaly detection in datasets using computer vision are classified accordingly.

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Metadata
Title
A Review of Anomaly Detection Techniques Using Computer Vision
Authors
Vandana Mohindru
Shafali Singla
Copyright Year
2021
Publisher
Springer Singapore
Book
Recent Innovations in Computing

Print ISBN: 978-981-15-8296-7

Electronic ISBN: 978-981-15-8297-4

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-981-15-8297-4_53

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