EURECOM and ECNU at TrecVid 2010 : The semantic indexing task
Мириам Реди · 2010
This year EURECOM and ECNU participated together at the TRECVID Semantic Indexing Task. We built four different systems for the light (10 concepts) submission. Three of our runs are functionally similar to the system used by EURECOM for last year’s High Level Feature Extraction task (see [6] for further details). We keep as a basic run (Fusebase) the best-performing system from 2009, testing how such system performs on the new dataset; we then improve the EURECOM Fusebase by adding a global descriptor, originally built for scene recognition, and proved to be effective in the TRECVID context for spatially-independent concepts like “Nighttime”. We then experiment with a multi-modal analysis, combining the visual features with the textual metadata that have been provided with the 2010 video database. As last run, we try a new system based on Hamming Embedding and Weighted Visual words. The runs are composed as follows: 1. EURECOM Fusebase This run fuses a pool of visual features, namely the Sift descriptor, the Color Moments global descriptor, the Wavelet Feature and the Edge Histogram. On top of this, a face detector and a re-ranking method based on the video knowledge are