This year the iAd-DCU team participated in three of the assigned TRECVid 2011 tasks; Semantic Indexing (SIN), Interactive Known-Item Search (KIS) and Multimedia Event Detection (MED). For the SIN task we presented three full runs using global features, local features and fusion of global, local features and relationships between concepts respectively. The evaluation results show that local features achieve better performance, with marginal gains found when introducing global features and relationships between concepts. With regard to our KIS submission, similar to our 2010 KIS experiments, we have implemented an iPad interface to a KIS video search tool. The aim of this year’s experimentation was to evaluate different display methodologies for KIS interaction. For this work, we integrate a clustering element for keyframes, which operates over MPEG-7 features using k-means clustering. In addition, we employ concept detection, not simply for search, but as a means of choosing most representative keyframes for ranked items. For our experiments we compare the baseline non-clustering system to a clustering system on a topic by topic basis. Finally, for the first time this year the iAd group at DCU has been involved in the MED Task. Two techniques are compared, employing low-level features directly and using concepts as intermediate representations. Evaluation results show promising initial results when performing event detection using concepts as intermediate representations.