TRECVID 2012 GENIE: Multimedia Event Detection and Recounting
A. G. Amitha Perera, Sangmin Oh, Megha Pandey, Tianyang Ma, Anthony J. Hoogs, Arash Vahdat, Kevin J. Cannons, Hossein Hajimirsadeghi, Greg Mori, Scott McCloskey, Ben Miller, Sharath Venkatesha, Pedro Davalos, Pradipto Das, Chenliang Xu, Jason J. Corso, Rohini K. Srihari, Ilseo Kim, You-Chi Cheng, Zhen Huang · 2012
Our MED 12 system is an extension of our MED 11 system [11], 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 score fusion. We have incorporated large number of audio-visual features in our new system and incorporated diverse types of standard and newly developed event agents which learn the salient audio-visual characteristics of event classes. The combination of additional features and newly developed powerful event agents improve our MED performance substantially beyond our MED 11 results. In addition, our MER 12 submissions reported recounting of specified clips for all five MER events and additionally provided MER results for all the clips detected by MED system. Our MER system generated recounting of detections based on CDR features and synopsis provided as part of the EventKits and DEV-T datasets. The MER evaluation results are promising for event-level discrimination, and indicated further improvement to be made for clip-level discrimination. 1