VideoQuest: managing large-scale aerial video database through automated content extraction

Hui Cheng; Darren Butler; Thomas Kover; Chris Meng

doi:10.1117/12.779696

14 April 2008 VideoQuest: managing large-scale aerial video database through automated content extraction

Hui Cheng, Darren Butler, Thomas Kover, Chris Meng

Proceedings Volume 6946, Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications V; 69460H (2008) https://doi.org/10.1117/12.779696
Event: SPIE Defense and Security Symposium, 2008, Orlando, Florida, United States

Abstract

Today, a large amount of videos is collected using aerial platforms. As the amount of aerial videos increases, there is an urgent need for effective management and systematic exploitation of aerial videos. In this paper, we introduce an aerial video management and exploitation system, named VideoQuest. The proposed system manages large-scale aerial video database through automated video processing and content extraction. These processing and content extraction algorithms include real-time video and metadata enhancement, hierarchical indexing and summarization, moving target detection (i.e. MTI), moving object tracking and event detection. Additionally, VideoQuest allows user to interactively search and browse large aerial video database based on sensor metadata and content extracted from aerial video. Using the VideoQeust system, a user can search and retrieve mission-relevant information several magnitudes faster than without using our system.

Citation Download Citation

Hui Cheng, Darren Butler, Thomas Kover, and Chris Meng "VideoQuest: managing large-scale aerial video database through automated content extraction", Proc. SPIE 6946, Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications V, 69460H (14 April 2008); https://doi.org/10.1117/12.779696

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