Semantic detection and recognition of objects and events contained in a video stream has to be performed in order to provide content-based annotation and retrieval of videos. This...
Lamberto Ballan, Marco Bertini, Alberto Del Bimbo,...
— Many image compression techniques require the quantization of multiple vector sources with significantly different distributions. With vector quantization (VQ), these sources ...
A clustering framework within the sparse modeling and dictionary learning setting is introduced in this work. Instead of searching for the set of centroid that best fit the data, ...
Pablo Sprechmann, Ignacio Ramirez, Guillermo Sapir...
Abstract. Segmentation is an important step to obtain quantitative information from tomographic data sets. To this end, global thresholding is often used in practice. However, it i...
Color quantization is the process of grouping n data points to k cluster. We proposed a new approach, based on Wu’s color quantization [6]. Our approach can significantly reduce ...