A new Video Synopsis Based Approach Using Stereo Camera
Talha Dilber, Mehmet Serdar Guzel, Erkan Bostanci

TL;DR
This paper introduces a novel video synopsis method that employs stereo cameras and object-based unsupervised learning to detect anomalies and generate concise summary videos by processing and analyzing object behaviors.
Contribution
The work presents a new approach combining stereo camera data with object tracking and anomaly detection for automatic video summarization.
Findings
Effective anomaly detection in video segments
Successful application to single and dual camera systems
Enhanced video summarization accuracy
Abstract
In today's world, the amount of data produced in every field has increased at an unexpected level. In the face of increasing data, the importance of data processing has increased remarkably. Our resource topic is on the processing of video data, which has an important place in increasing data, and the production of summary videos. Within the scope of this resource, a new method for anomaly detection with object-based unsupervised learning has been developed while creating a video summary. By using this method, the video data is processed as pixels and the result is produced as a video segment. The process flow can be briefly summarized as follows. Objects on the video are detected according to their type, and then they are tracked. Then, the tracking history data of the objects are processed, and the classifier is trained with the object type. Thanks to this classifier, anomaly behavior…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsVideo Analysis and Summarization · Advanced Vision and Imaging · Video Coding and Compression Technologies
