Title
TNO at TRECVID 2013: Multimedia Event Detection and Instance Search
Author
Bouma, H.
Azzopardi, G.
Spitters, M.M.
de Wit, J.J.
Versloot, C.A.
van der Zon, R.W.L.
Eendebak, P.T.
Baan, J.
ten Hove, R.J.M.
van Eekeren, A.W.M.
ter Haar, F.B.
den Hollander, R.J.M.
van Huis, R.J.
de Boer, M.H.T.
van Antwerpen, G.
Broekhuijsen, B.J.
Daniele, L.M.
Brandt, P.
Schavemaker, J.G.M.
Kraaij, W.
Schutte, K.
Publication year
2013
Abstract
We describe the TNO system and the evaluation results for TRECVID 2013 Multimedia Event Detection (MED) and instance search (INS) tasks. The MED system consists of a bag-of-word (BOW) approach with spatial tiling that uses low-level static and dynamic visual features, an audio feature and high-level concepts. Automatic speech recognition (ASR) and optical character recognition (OCR) are not used in the system. In the MED case with 100 example training videos, support-vector machines (SVM) are trained and fused to detect an event in the test set. In the case with 0 example videos, positive and negative concepts are extracted as keywords from the textual event description and events are detected with the high-level concepts. The MED results show that the SIFT keypoint descriptor is the one which contributes best to the results, fusion of multiple low-level features helps to improve the performance, and the textual event-description chain currently performs poorly. The TNO INS system presents a baseline open-source approach using standard SIFT keypoint detection and exhaustive matching. In order to speed up search times for queries a basic map-reduce scheme is presented to be used on a multi-node cluster. Our INS results show above-median results with acceptable search times.
Subject
TS - Technical Sciences
Physics & Electronics ; Communication & Information
Information Society
Infostructures
Event Detection
Video
II - Intelligent Imaging ; BIS - Business Information Services ; MNS - Media & Network Services
To reference this document use:
http://resolver.tudelft.nl/uuid:b7639a65-8871-4d15-beac-8e930ff3d704
TNO identifier
485250
Publisher
NIST
Source
Proceedings of TRECVID 2013
Document type
conference paper