Building 3D event logs for video investigation

In scene investigation, creating a video log captured using a handheld camera is more convenient and more complete than taking photos and notes. By introducing video analysis and computer vision techniques, it is possible to build a spatio-temporal representation of the investigation. Such a representation gives a better overview than a set of photos and makes an investigation more accessible. We develop such methods and present an interface for navigating the result. The processing includes (i) segmenting a log into events using novel structure and motion features making the log easier to access in the time dimension, and (ii) mapping video frames to a 3D model of the scene so the log can be navigated in space. Our results show that, using our proposed features, we can recognize more than 70 percent of all frames correctly, and more importantly find all the events. From there we provide a method to semi-interactively map those events to a 3D model of the scene. With this we can map more than 80 percent of the events. The result is a 3D event log that captures the investigation and supports applications such as revisiting the scene, examining the investigation itself, or hypothesis testing.

Title:	Building 3D event logs for video investigation
Authors:	Dang, Trung Kien Worring, Marcel Bui, The Duy
Keywords:	Video analysis;Story navigation;Scene investigation;3D model
Issue Date:	2015
Publisher:	Kluwer Academic Publishers
Citation:	Scopus
Abstract:	In scene investigation, creating a video log captured using a handheld camera is more convenient and more complete than taking photos and notes. By introducing video analysis and computer vision techniques, it is possible to build a spatio-temporal representation of the investigation. Such a representation gives a better overview than a set of photos and makes an investigation more accessible. We develop such methods and present an interface for navigating the result. The processing includes (i) segmenting a log into events using novel structure and motion features making the log easier to access in the time dimension, and (ii) mapping video frames to a 3D model of the scene so the log can be navigated in space. Our results show that, using our proposed features, we can recognize more than 70 percent of all frames correctly, and more importantly find all the events. From there we provide a method to semi-interactively map those events to a 3D model of the scene. With this we can map more than 80 percent of the events. The result is a 3D event log that captures the investigation and supports applications such as revisiting the scene, examining the investigation itself, or hypothesis testing.
Description:	Multimedia Tools and Applications, Volume 74, Issue 13, 2 June 2015, Pages 4617-4639
URI:	http://link.springer.com/article/10.1007%2Fs11042-013-1826-9 http://repository.vnu.edu.vn/handle/VNU_123/32331
ISSN:	13807501
Appears in Collections:	Bài báo của ĐHQGHN trong Scopus