Dominique Maniry

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—This paper presents a deep neural network-based approach to image quality assessment (IQA). The network can be trained end-to-end and comprises 10 convolutional layers and 5 pooling layers for feature extraction, and 2 fully connected layers for regression, which makes it significantly deeper than related IQA methods. An unique feature of the proposed(More)
This paper describes the participation of the TUB-IRML group to the MediaEval 2014 Visual Privacy task. We present a method for privacy protection of individuals in surveillance videos. In order to achieve this, our method obscures both shape and appearance of identity-related regions through blurring and color remapping. The intelligibility is preserved by(More)
In this paper, we present a method for removing identity-related information from image sequences for the privacy protection of individuals. The face, despite being an important feature to identify a person, is not the only body part that needs to be obscured. Therefore, we propose to replace the whole body of individuals by their silhouette defined by(More)
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