Event Oriented Dictionary Learning for Complex Event Detection

doi:10.1109/TIP.2015.2413294

Event Oriented Dictionary Learning for Complex Event Detection

2015-06-01

107

OA

AI

Alexander G. Hauptmann

N

Nicu Sebe

DOI：10.1109/TIP.2015.2413294

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Complex event detection is a retrieval task with the goal of finding videos of a particular event in a large-scale unconstrained Internet video archive, given example videos and text descriptions. Nowadays, different multimodal fusion schemes of low-level and high-level features are extensively investigated and evaluated for the complex event detection task. However, how to effectively select the high-level semantic meaningful concepts from a large pool to assist complex event detection is rarely studied in the literature. In this paper, we propose a novel strategy to automatically select semantic meaningful concepts for the event detection task based on both the events-kit text descriptions and the concepts high-level feature descriptions. Moreover, we introduce a novel event oriented dictionary representation based on the selected semantic concepts. Toward this goal, we leverage training images (frames) of selected concepts from the semantic indexing dataset with a pool of 346 concepts, into a novel supervised multitask l(p)-norm dictionary learning framework. Extensive experimental results on TRECVID multimedia event detection dataset demonstrate the efficacy of our proposed method.

Keywords:

Complex event detection

concept selection

event oriented dictionary learning

supervised multi-task dictionary learning

Event Oriented Dictionary Learning for Complex Event Detection

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