Paper Info
Title
Autopiloting Feature Maps: The Deep Interactive Video Exploration (diveXplore) System at VBS2019.
Abstract
We present the most recent version of our Deep Interactive Video Exploration (diveXplore) system, which has been successfully used for the latest two Video Browser Showdown competitions (VBS2017 and VBS2018) as well as for the first Lifelog Search Challenge (LSC2018). diveXplore is based on a plethora of video content analysis and processing methods, such as simple color, texture, and motion analysis, self-organizing feature maps, and semantic concept extraction with different deep convolutional neural networks. The biggest strength of the system, however, is that it provides a variety of video search and rich interaction features. One of the novelties in the most recent version is a Feature Map Autopilot, which ensures time-efficient inspection of feature maps without gaps and unnecessary visits.
Year
Venue
Field
2019
MMM
Interactive video,Computer vision,Lifelog,Video retrieval,Computer science,Convolutional neural network,Video content analysis,Autopilot,Artificial intelligence,Concept extraction,Motion analysis
DocType
Citations 
PageRank 
Conference
0
0.34
References 
Authors
4
5
Name
Order
Citations
PageRank
Klaus Schoeffmann150963.01
Bernd Münzer29814.94
Andreas Leibetseder3229.82
Jürgen Primus410.71
Sabrina Kletz5217.71