Titlebook: Anomaly Detection in Video Surveillance; Xiaochun Wang Book 2024 The Editor(s) (if applicable) and The Author(s), under exclusive license

搖擺

Sparse Representation-Based Video Anomaly Detection Approaches,cenes. Generally, crowd abnormal behaviors cannot be treated as a simple collection of individual behaviors in the form of trajectories due to the occlusion that happens among them. One solution would be to treat the crowd as a single entirety in a specific scene and detect the anomaly by analyzing

綁架

Thyroxine

細(xì)菌等

Seminar

草率女

Regression-Based Video Anomaly Detection Approaches,t in most cases contain little or no annotation for supervised learning. This chapter introduces the state-of-the-art deep learning-based methods that make use of the past history of the video data to provide a prediction of the pattern for?the future video images and use the difference between the

inculpate

歌劇等

Mathematical Preliminaries for Video Anomaly Detection Techniques,some of the?concepts in probability and statistics and information theory are briefly reviewed. We will also look at some knowledge of neural networks that leads to the cutting-edge deep learning-based techniques.

thalamus

Optical Flow-Based Video Anomaly Detection Approaches, behaviors, it also can be used as a motion feature extraction method for other abnormal behavior detection methods. As an illustration, a number of ways to use optical flow for anomaly detection are described.

序曲

Book 2024ic and industrial value. The key advantage of writing the book at this point in time is that the vast amount of work done by computer scientists over the last few decades has remained largely untouched by a formal book on the subject, although these techniques significantly advance existing methods