Informedia e-lamp @ TRECVID 2012 multimedia event detection and recounting MED and MER
Yu, SI
Xu, Z
Ding, D
Sze, W
Vicente, F
Lan, Z
Cai, Y
Rawat, S
Schulam, P
Markandaiah, N
Bahmani, S
Juarez, A
Tong, W
Yang, Y
Burger, S
Metze, F
Singh, R
Raj, B
Stern, R
Mitamura, T
Nyberg, E
Hauptmann, A
Burger, S
Metze, F
Singh, R
Raj, B
Stern, R
Mitamura, T
Nyberg, E
Hauptmann, A
- Publication Type:
- Conference Proceeding
- Citation:
- 2012 TREC Video Retrieval Evaluation Notebook Papers, 2012
- Issue Date:
- 2012-01-01
Closed Access
| Filename | Description | Size | |||
|---|---|---|---|---|---|
| Informedia E-Lamp@TRECVID 2012- Multimedia Event Detection and Re.pdf | Published version | 2.42 MB |
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We report on our system used in the TRECVID 2012 Multimedia Event Detection (MED) and Multimedia Event Recounting (MER) tasks. For MED, it consists of three main steps: extracting features, training detectors and fusion. In the feature extraction part, we extract many low-level, high-level, 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 the official sources and our internal evaluations show good performance of our system. Our MER system utilizes a subset of features and detection results from the MED system from which the recounting is generated.
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