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We propose an image restoration technique exploiting regularized inversion and the recent block-matching and 3D filtering (BM3D) denoising filter. The BM3D employs a non-local modeling of images by collecting similar image patches in 3D arrays. The so-called collaborative filtering applied on such a 3D array is realized by transform-domain shrinkage. In(More)
We propose an e¤ ective video denoising method based on highly sparse signal representation in local 3D transform domain. A noisy video is processed in blockwise manner and for each processed block we form a 3D data array that we call " group " by stacking together blocks found similar to the currently processed one. This grouping is realized as a(More)
We propose an effective color image denoising method that exploits ltering in highly sparse local 3D transform domain in each channel of a luminance-chrominance color space. For each image block in each channel, a 3D array is formed by stacking together blocks similar to it, a process that we call " grouping ". The high similarity between grouped blocks in(More)
— Nowadays most camera-enabled electronic devices contain various auxiliary sensors such as accelerometers, gyroscopes, compasses, GPS receivers, etc. These sensors are often used during the media acquisition to limit camera degradations such as shake and also to provide some basic tagging information such as the location used in geo-tagging. Surprisingly,(More)
In this work we propose to exploit context sensor data for analyzing user generated videos. Firstly, we perform a low-level indexing of the recorded media with the instantaneous compass orientations of the recording device. Subsequently, we exploit the low level indexing to obtain a higher level indexing for discovering camera panning movements, classifying(More)
License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. User-generated video content has grown tremendously fast to the point of outpacing professional content creation. In this work we develop methods that analyze contextual information of multiple user-generated videos in order(More)
In this work we propose methods that exploit context sensor data modalities for the task of detecting interesting events and extracting high-level contextual information about the recording activity in user generated videos. Indeed, most camera-enabled electronic devices contain various auxiliary sensors such as accelerometers, compasses, GPS receivers,(More)
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