Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Desai Fan

dblp:195/8163 · DBLP profile ↗
← Back
1ranked-venue papers
0as first author
0since 2021 · last 2017
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1Graphics, computer vision, multimedia, augmented reality and games · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
1 paper
Multimedia analysis and retrieval · 67% Image and video processing · 33%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Image and video processing › image reconstruction
event-based image reconstruction
0.312017
An Event Reconstruction Tool for Conflict Monitoring Using Social Media · AAAI 2017
Multimedia analysis and retrieval › object tracking
person tracking
0.312017
An Event Reconstruction Tool for Conflict Monitoring Using Social Media · AAAI 2017
Multimedia analysis and retrieval
video analysis
0.312017
An Event Reconstruction Tool for Conflict Monitoring Using Social Media · AAAI 2017

Methods — techniques the papers use, named apart from their topics

video synchronization · 0.3geolocalization · 0.33d reconstruction · 0.3
YearPublicationVenuePosition
2017 An Event Reconstruction Tool for Conflict Monitoring Using Social Media
abstract
What happened during the Boston Marathon in 2013? Nowadays, at any major event, lots of people take videos and share them on social media. To fully understand exactly what happened in these major events, researchers and analysts often have to examine thousands of these videos manually. To reduce this manual effort, we present an investigative system that automatically synchronizes these videos to a global timeline and localizes them on a map. In addition to alignment in time and space, our system combines various functions for analysis, including gunshot detection, crowd size estimation, 3D reconstruction and person tracking. To our best knowledge, this is the first time a unified framework has been built for comprehensive event reconstruction for social media videos.
Junwei Liang 0001, Desai Fan, Po-Yao Huang 0001, Jia Chen 0001, Lu Jiang 0004, Alex Hauptmann 0001
AAAI2