TRECVID 2013 GENIE: Multimedia event detection and recounting

Sangmin Oh, A. G. Amitha Perera, Ilseo Kim, Megha Pandey, Kevin Cannons, Hossein Hajimirsadeghi, Arash Vahdat, Greg Mori, Ben Miller, Scott McCloskey, You Chi Cheng, Zhen Huang, Chin Hui Lee, Chenliang Xu, Rohit Kumar, Wei Chen, Jason Corso, L. Fei-Fei, Daphne Koller, Vignesh RamanathanKevin Tang, Armand Joulin, Alexandre Alahi

Research output: Contribution to conferencePaperpeer-review

Abstract

Our MED 13 system is an extension of our MED 12 system [12, 13], and consists of a collection of low-level and high-level features, feature-specific classifiers built upon those features, and a fusion system that combines features both through mid-level kernel fusion and late fusion. Our MED submissions include total of 24 different configurations which consist of combinations of 2 submission timings (PS/AH), 3 training conditions (100/10/0Ex), and 4 types of feature conditions (Full/Visual/Audio/ASR). Our MER 13 submissions reported recounting for all five MER events. Our MER system combines evidences from multiple base classifiers, which are translated to texts and used to identify key frames. Multiple MER results are fused and presented to users as recounting for each detection.

Original languageEnglish
StatePublished - 2013
Event2013 TREC Video Retrieval Evaluation, TRECVID 2013 - Gaithersburg, United States
Duration: 20 Nov 201322 Nov 2013

Conference

Conference2013 TREC Video Retrieval Evaluation, TRECVID 2013
Country/TerritoryUnited States
CityGaithersburg
Period20/11/1322/11/13

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