Anomaly Detection: Explanation & Implementation

This video will teach you -
What is Anomaly detection?
How Anomaly detection algorithm work?
Implementation of Anomaly detection code of this paper: arxiv.org/pdf/1801.04264v3
GitHub: github.com/AarohiSingla/Anoma...
Email id : [e-mail]
The paper proposes a method for learning anomalies in surveillance videos without the need for annotating anomalous segments, which can be ti me-consuming. Instead, it suggests leveraging weakly labeled training videos, where the labels (anomalous or normal) are assigned at the video level rather than the clip level.
The paper introduces a new large-scale dataset consisting of 128 hours of real-world surveillance videos, containing various anomalies such as fighting, road accidents, burglary, robbery, etc., along with normal activities. This dataset serves two purposes: general anomaly detection considering all anomalies as one group and all normal activities as another group, and recognizing each of the 13 anomalous activities individually.
Goal:
The ultimate goal of the proposed system is to enhance the efficiency of video surveillance by automatically detecting anomalous events, such as traffic accidents or crimes, without the need for extensive human monitoring.
This contributes to public safety by enabling timely detection and response to unusual activities captured by surveillance cameras.
Proposed Anomaly Detection Method:
The approach treats normal and anomalous videos as "bags" and video segments as "instances"
The proposed approach begins with dividing surveillance videos into a fixed number of segments during training. These segments make instances in a bag. Using both positive (anomalous) and negative (normal) bags, we train the anomaly detection model using the proposed deep MIL ranking loss.
Proposed dataset:
the paper introduces a new large-scale dataset consisting of 128 hours of real-world surveillance videos, containing various anomalies such as fighting, road accidents, burglary, robbery, etc., along with normal activities. This dataset serves two purposes: general anomaly detection considering all anomalies as one group and all normal activities as another group, and recognizing each of the 13 anomalous activities individually.
We divide our dataset into two parts: the training set consisting of 800 normal and 810 anomalous videos (details shown in Table 2) and the testing set including the remaining 150 normal and 140 anomalous videos. Both training and testing sets contain all 13 anomalies at various temporal locations in the videos. Furthermore, some of the videos have multiple anomalies.
#computervision #anomaly #anomalydetection #artificialintelligence #deeplearning

[@soravsingla8782]

Impressive content

[@user-uq1qq7pj8h]

Happy Teacher’s Day Madam❤️✨ You are truly and inspiration and thanks for being there for us. Please take care and you always hold a special place in my heart❤️✨

[@CodeWithAarohi]

You are so welcome :)

[@md.habiburrahamanashik8980]

Thanks for your impressive contents.

[@CodeWithAarohi]

Glad you like them!

[@pifordtechnologiespvtltd5698]

Keep it up

[@CodeWithAarohi]

Thanks!

[@FirstNameLastName-fv4eu]

As usual You are the best!!

[@CodeWithAarohi]

Thank you!

[@bay-bicerdover]

Wow! 👏🏻

[@CodeWithAarohi]

Thank you :)

[@arnavthakur5409]

Very nicely explained. Thank you ma'am

[@CodeWithAarohi]

Most welcome 😊

[@angelospapadopoulos7679]

nice one!

[@CodeWithAarohi]

Thanks!

[@SMustafaBasturk]

Hello, I appreciate your work. However, when I went a little deeper into the project, I saw that the c3d model performed very poorly in alternative videos. Is there another source you can give for using other models such as i3d models? I wanted to ask you because it is impossible for me to train this i3d model on my own computer. So I am waiting for your answer 🙏

[@CodeWithAarohi]

I don't have any sources for that. Sorry

[@corentink3887]

is there no issue with memory management ? I assume segment size can get pretty big and cause issue if it is passed in paralell

[@CodeWithAarohi]

No issue with memory management

[@sw_2421]

Hello ma'am can u give us some tutorials on how to implement research papers of ml dl..

[@CodeWithAarohi]

I will try to make

[@jayathissaaral2598]

git hub link doesnt work

[@CodeWithAarohi]

It is working now. Please check

[@fahimmahafuzruhad9485]

please upload a vedio using it in google colab

[@CodeWithAarohi]

I will do but till there are no changes in the code whether you are running it on local pc or colab. Just upload this entire code to google drive and run the video_demo.py file from your colab. You only need to take care of paths. Just change the paths where ever required.

[@fahimmahafuzruhad9485]

@@CodeWithAarohi Thank you mam