ARTEMIS.Ubimedia at TRECVID 2012: Instance Search Task.
Andrei Bursuc, Titus B. Zaharia, Olivier Martinot, Francoise J. Preteux · 2012
Abstract. This paper describes the approach proposed by ARTEMIS-UBIMEDIA team at TRECVID 2012, Instance Search (INS) task [1]. The method is based on the Bag-of-Words representation obtained from uniform sampling of the frames of the videos. We propose a query expansion technique that employs the textual description of the queries to identify new instances of the query objects on Flickr in order to enrich the query descriptor with additional representative instances. Briefly, what approach or combination of approaches did you test in each of your submitted runs? (please use the run id from the overall results table NIST returns) all runs: 1 frame per second sampling from the videos, frames resized to 384x288 surface, Hessian Affine detectors and RootSIFT descriptor. F_X_NO_UbiBWVTR_1: BoW vectors generated at shot level. Single query BoW vector generated from the multiple example images. F_X_NO_UbiBWVHF_2: BoW vectors generated at shot level. Query BoW vectors generated from images fetched from Flickr using the provided query textual description. F_X_NO_UbiBWFFM_3: BoW vectors generated for each frame and for each query image. The score