Object knowledge modulates colour appearance

We investigated the memory colour effect for colour diagnostic artificial objects. Since knowledge about these objects and their colours has been learned in everyday life, these stimuli allow the investigation of the influence of acquired object knowledge on colour appearance. These investigations are relevant for questions about how object and colour information in high-level vision interact as well as for research about the influence of learning and experience on perception in general. In order to identify suitable artificial objects, we developed a reaction time paradigm that measures (subjective) colour diagnosticity. In the main experiment, participants adjusted sixteen such objects to their typical colour as well as to grey. If the achromatic object appears in its typical colour, then participants should adjust it to the opponent colour in order to subjectively perceive it as grey. We found that knowledge about the typical colour influences the colour appearance of artificial objects. This effect was particularly strong along the daylight axis

o.OM: Structured-Functional Communication between Computer Music Systems using OSC and Odot

International audienceO.—odot—is a portable media programming framework based on the OSC data encoding. It embeds a small expression language which allows writing and executing programs in OSC structures. The integration of programming and declarative functional descriptions within data transfer protocols enables structured and expressive communication in media systems: program snippets can be distributed in OSC messages, which evaluate to further OSC messages in the different communicating software. We present experiments using this framework in the OpenMusic computer-aided composition environment , and illustrate via case studies some advantages of such integrated system

User Controllable Color Transfer

This paper presents an image editing framework where users use reference images to indicate desired color edits. In our approach, users specify pairs of strokes to indicate corresponding regions in both the original and the reference image that should have the same color “style”. Within each stroke pair, a nonlinear constrained parametric transfer model is used to transfer the reference colors to the original. We estimate the model parameters by matching color distributions, under constraints that ensure no visual artifacts are present in the transfer result. To perform transfer on the whole image, we employ optimization methods to propagate the model parameters defined at each stroke location to spatially-close regions of similar appearance. This stroke-based formulation requires minimal user effort while retaining the high degree of user control necessary to allow artistic interpretations. We demonstrate our approach by performing color transfer on a number of image pairs varying in content and style, and show that our algorithm outperforms state-of-the-art color transfer methods on both user-controllability and visual qualities of the transfer results