Anomaly detection in video
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Anomaly detection in video
Anomaly Detection in VideobyTran Thi Minh HanhSubmitted in accordance with the requirements for the degree of Doctor of PhilosophyThe University of Le Anomaly detection in video eeds School of Computing June 2018DeclarationsThe candidate confirms that the work submitted is his/her own. except where work which has formed part of a jointly authored publication has been included. The contribution of the candidate and the other authors to this work has been explicitly indicated Anomaly detection in video below. The candidate confirms that appropriate credit has been given within the thesis where reference has been made to the work of others.Some partsAnomaly detection in video
of the w ork presented in this thesis have been published in the following articles:Hanh T. M. Tran and David c. Hogg. Anomaly Detection using a ConvAnomaly Detection in VideobyTran Thi Minh HanhSubmitted in accordance with the requirements for the degree of Doctor of PhilosophyThe University of Le Anomaly detection in video s that the above jointly-authored publications are primarily the work of the first author. The role of the second author w as purely supcrv isory.This copy has been supplied on the understanding that it is copyright material and that no quotation from the thesis may be published without proper ackno Anomaly detection in video wledgement.©2018 The University of Leeds and Tran Thi Minh HanhAbstractAnomaly detection is an area of video analysis that has great importance in autAnomaly detection in video
omated surveillance. Although it has been extensively studied, there has been little work on using deep convolutional neural networks to learn spatio-Anomaly Detection in VideobyTran Thi Minh HanhSubmitted in accordance with the requirements for the degree of Doctor of PhilosophyThe University of Le Anomaly detection in video s for anomaly detection.The contributions are divided into two main chapters. The first introduces a method that uses a convolutional autoencoder to learn motion features from foreground optical I low patches. The autocncoder is coupled with a spatial sparsity constraint, known as Winner-Take-All, t Anomaly detection in video o learn shift-invariant and generic flow-features. This method solves the problem of using hand-crafted feature representations in state of the an metAnomaly detection in video
hods. Moreover, to capture variations in scale of the patterns of motion as an object moves in depth through the scene, we also divide the image planeAnomaly Detection in VideobyTran Thi Minh HanhSubmitted in accordance with the requirements for the degree of Doctor of PhilosophyThe University of Le Anomaly detection in video ate improved performance.The second main chapter presents a end-to-end method that learns normal spatiotemporal dynamics from video volumes using a scqucncc-to-scqucnce encoder-decoder for prediction and reconstruction. This work is based on the intuition that the encoder-decoder learns to estimate Anomaly detection in video normal sequences in a training set with low error, thus it estimates an abnormal sequence with high error. Error between the network's output and theAnomaly detection in video
target output is used to classify a video volume as normal or abnormal. In addition to the use of reconstruction error, we also use prediction error fAnomaly Detection in VideobyTran Thi Minh HanhSubmitted in accordance with the requirements for the degree of Doctor of PhilosophyThe University of Le Anomaly detection in video In comparison with the first proposed method, performance is improved in one dataset. Moreover, running time is significantly faster.iiAcknowledgementsFirst of all 1 would like lo express my utmost gratitude to my supervisor Prof. David Hogg. His guidance, feedback and encouragement have inspired m Anomaly detection in video e to pursue novel ideas and he have helped me to develop the research skills. I would also like to thank him and the department for funding me for varAnomaly detection in video
ious events such as a summer school and conferences during my PhD.My sincere gratitude goes to Project 91 I - Vietnam International Education DepartmeAnomaly Detection in VideobyTran Thi Minh HanhSubmitted in accordance with the requirements for the degree of Doctor of PhilosophyThe University of Le Anomaly detection in video my PhD at University of Leeds.Also a big thank you to all current and ex PhD students. Ary ana Tavanai. Christiana Panayi, I.co Pauly. Rebecca Stone and so many others who have discussed ideas and helped me over the last four years. .My special thanks go to Duane Carey and Fouzhan Hosseini who have Anomaly detection in video advised and encouraged me through the hardest limes. 1 would also like to thank the staff in the School of Computing for a lot of fruitful discussionAnomaly detection in video
s and support, and for providing a conductive environment to research. There arc many others, too many to list here, but my gratitude goes to everyoneAnomaly Detection in VideobyTran Thi Minh HanhSubmitted in accordance with the requirements for the degree of Doctor of PhilosophyThe University of Le Anomaly detection in video nam. Without the never ending support and encouragement of my parents. 1 would not be here now. I would also like to thank my husband. Nguyen Van Quycn, who has supported me at the toughest times, understanding w hen I was so caught up in my work and encouraging me when things went wrong. My special Anomaly detection in video thanks go to my lovely son. who has brought so much joy laughter and happiness into my PhD.iiiContents1Introduction11.1Challenges....................Anomaly detection in video
....................................... 21.2Motivation........................................................... 31.3Aims and Objectives.............Anomaly Detection in VideobyTran Thi Minh HanhSubmitted in accordance with the requirements for the degree of Doctor of PhilosophyThe University of Le Anomaly detection in video .................................1.6Outline ............................................................. 72Related Work92.1Introduction......................................................... 9 Anomaly detection in video Anomaly Detection in VideobyTran Thi Minh HanhSubmitted in accordance with the requirements for the degree of Doctor of PhilosophyThe University of LeGọi ngay
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