This paper describes the participation of VITALAS in the TRECVID-2009 evaluation where we submitted runs for the High-Level Feature Extraction (HLFE) and Interactive Search tasks. For the HLFE task, we focus on the evaluation of low-level feature sets and fusion methods. The runs employ multiple low-level features based on all available modalities (visual, audio and text) and the results show that use of such features improves the retrieval e ectiveness signi cantly. We also use a concept score fusion approach that achieves good results with reduced low-level feature vector dimensionality. Furthermore, a weighting scheme is introduced for cluster assignment in the \bag-of-words" approach. Our runs achieved good performance compared to a baseline run and the submissions of other TRECVID-2009 participants. For the Interactive Search task, we focus on the evaluation of the integrated VITALAS system in order to gain insights into the use and e ectiveness of the system's search functionalities on (the combination of) multiple modalities and study the behavior of two user groups: professional archivists and non-professional users. Our analysis indicates that both user groups submit about the same total number of queries and use the search functionalities in a similar way, but professional users save twice as many shots and examine shots deeper in the ranked retrieved list.The agreement between the TRECVID assessors and our users was quite low. In terms of the e ectiveness of the di erent search modalities, similarity searches retrieve on average twice as many relevant shots as keyword searches, fused searches three times as many, while concept searches retrieve even up to ve times as many relevant shots, indicating the bene ts of the use of robust concept detectors in multimodal video retrieval. High-Level Feature Extraction Runs 1. A VITALAS.CERTH-ITI 1: Early fusion of all available low-level features. 2. A VITALAS.CERTH-ITI 2: Concept score fusion for ve low-level features and 100 concepts, text features and bag-of-words with color SIFT descriptor based on dense sampling. 3. A VITALAS.CERTH-ITI 3: Concept score fusion for ve low-level features and 100 concepts combined with text features. 4. A VITALAS.CERTH-ITI 4: Weighting scheme for bag-of-words based on dense sampling of the color SIFT descriptor. 5. A VITALAS.CERTH-ITI 5: Baseline run, bag-of-words based on dense sampling of the color SIFT descriptor. Interactive Search Runs 1. vitalas 1: Interactive run by professional archivists 2. vitalas 2: Interactive run by professional archivists 3. vitalas 3: Interactive run by non-professional users 4. vitalas 4: Interactive run by non-professional users

NIST
TRECVID Workshop
Human-Centered Data Analytics

Diou, C., Stephanopoulos, G., Dimitriou, N., Panagiotopoulos, P., Papachristou, C., Delopoulos, A., … CWI et al, . not . (2009). VITALAS at TRECVID-2009. In Proceedings of the 7th TREC Video Retrieval Evaluation Workshop. NIST.