Carnegie Mellon University
file.pdf (2.24 MB)

Informedia E-Lamp@TRECVID 2012: Multimedia Event Detection and Recounting (MED and MER)

Download (2.24 MB)
journal contribution
posted on 2012-01-01, 00:00 authored by Shoou-I Yu, Zhongwen Xu, Duo Ding, Waito Sze, Francisco Vicente, Zhenzhong Lan, Yang CaiYang Cai, Shourabh Rawat, Peter F. Schulam, Sohail Bahmani, Antonio Juarez, Wei Tong, Yi Yang, Susanne Burger, Florian MetzeFlorian Metze, Rita Singh, Bhiksha Raj, Roxana SarbuRoxana Sarbu, Teruko Mitamura, Eric Nyberg, Alexander Hauptmann

We report on our system used in the TRECVID 2012 Multimedia Event Detection (MED) and Multimedia Event Recounting (MER) tasks. For MED, generally, it consists of three main steps: extracting features, training detectors and fusion. In the feature extraction part, we extract many low-level, high-level features and text features. Those features are then represented in three different ways which are spatial bag-of words with standard tiling, spatial bag-of-words with feature and event specific tiling and the Gaussian Mixture Model Super Vector. In the detector training and fusion, two classifiers and three fusion methods are employed. The results from both of the official sources and our internal evaluations show good performance of our system. For our MER system, it takes some of the features and detection results from the MED system from which the recount is then generated.




Usage metrics


    Ref. manager