Dimensionality reduction is an important issue when facing high-dimensional data. For supervised dimensionality reduction, Linear Discriminant Analysis (LDA) is one of the most po...
Feiping Nie, Shiming Xiang, Yangqiu Song, Changshu...
When colourimetrically characterising a high dynamic range display (HDR) built from an LCD panel and an LED backlight one is faced with several problems: the channels may not be c...
Alexa I. Ruppertsberg, Marina Bloj, Francesco Bant...
Recovering 3D geometry from a single view of an object is an important and challenging problem in computer vision. Previous methods mainly focus on one specific class of objects ...
Traditional image compression techniques seek the smallest possible le size for a given level of image quality. By contrast, network-conscious image compression techniques take in...
Paul D. Amer, Sami Iren, Gul E. Sezen, Phillip T. ...
Three-dimensional appearance models consisting of spatially varying reflectance functions defined on a known shape can be used in analysis-by-synthesis approaches to a number of vi...
Todd Zickler, Ravi Ramamoorthi, Sebastian Enrique,...