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The reconstruction of 3D city models has matured to the point where large data sets are now available. As most of the data collection methods used are based on airborne sensors like e.g. aerial laser...
What if the touchscreen of your smartphone or tablet could touch you back? What if touch was as integrated into our ubiquitous technology as sight and sound? Northwestern University and Carnegie Mell...
In this paper, we propose a novel dynamic texture description method base on spatiotemporal context phrase for general dynamic texture. Different with the existing methods, we consider the spatiotempo...
The proposed method aims to provide a new tool for texture recognition. For this purpose, a set of texture samples are decomposed by using the FastICA algorithm and characterized by a negentropy based...
In 3D video applications, the virtual view is generally rendered by the compressed texture and depth. The texture and depth compression with different bit-rate overheads can lead to different virtual ...
In this paper, we propose a novel background subtraction algorithm, which takes both texture and motion information into account. Texture information is represented by local binary pattern (LBP), whic...
In this paper, we present a novel approach to classify texture collections. This approach does not require experts to provide annotated training set. Given the image collection, we extract a set of in...
Purpose: Owing to the complexity of machined surface profiles and the contemporary demands for functional characterization, multi- parameter analysis of roughness is recommended by international surfa...
In this paper we propose a motion based approach for synthesizing dynamic textures. Dynamic textures are natural phenomenon characterized by their distinctive motion patterns. Synthesis of these textu...
In this paper, we propose a novel hybrid de-interlacing algorithm, which effectively combines two motioncompensated (MC) de-interlacing techniques: MC Median Filtering (MCMF) and Adaptive Recursive (A...
In this paper, we present a novel approach to classify texture collections. This approach does not require experts to provide annotated training set. Given the image collection, we extract a set of i...
The method proposed in this paper uses the Independent Component Analysis (ICA) for an application of unsupervised recognition of textures. The analysed texture is modelled by a weighted sum of almost...
In this paper, we propose a new algorithm for remotely sensed image texture classification and segmentation. We observe that the traditional method least square error (LSE) is unstable in practical ap...

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