CORDIS Project
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This project focuses on recognizing human actions in video data by analyzing object interactions. It aims to improve the accuracy of motion and object recognition by integrating information from multiple frames to create detailed representations of actions and their contexts.
This proposal addresses recognition of object guided human actions in video data.
Automation of the analysis requires advances in human motion recognition, object recognition in video as well as incorporation of action-object relations.
Recognition in video is challenging due to dramatic changes in appearance between frames, low resolution and blur.
In this work I intend to incorporate information from multiple frames at all levels of processing to overcome these difficulties.
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