Event Oriented Dictionary Learning for Complex Event Detection PROJECT TITLE :Event Oriented Dictionary Learning for Complex Event DetectionABSTRACT:Complicated event detection is a retrieval task with the goal of finding videos of a particular event in an exceedingly 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 complicated event detection task. However, how to effectively select the high-level semantic meaningful ideas from a giant pool to assist complex event detection is rarely studied within the literature. During this paper, we have a tendency to propose a novel strategy to automatically choose semantic meaningful ideas for the event detection task based on each the events-kit text descriptions and therefore the ideas high-level feature descriptions. Moreover, we tend to introduce a novel event oriented dictionary illustration primarily based on the selected semantic ideas. Toward this goal, we have a tendency to leverage training pictures (frames) of selected ideas from the semantic indexing dataset with a pool of 346 concepts, into a novel supervised multitask $ell !_p$ -norm dictionary learning framework. Intensive experimental results on TRECVID multimedia event detection dataset demonstrate the efficacy of our proposed technique. Did you like this research project? To get this research project Guidelines, Training and Code... Click Here facebook twitter google+ linkedin stumble pinterest Stop and Think: Exploring Mobile Notifications to Foster Reflective Practice on Meta-Learning Calibration and Validation of ZY-3 Optical Sensors