Experimental validation of colour rendition specification criteria based on ANSI/IES TM-30-18

An experiment was conducted to examine colour rendition specification criteria. Twenty-five participants each evaluated 90 lighting scenes in a room filled with objects. The lighting scenes included nine chromaticity groups, each with 10 systematically-varied colour rendition conditions designed to meet or not meet previously proposed colour preference specification criteria using the ANSI/IES TM-30-18 measures: Fidelity Index ( Rf), Gamut Index ( Rg) and red Local Chroma Shift ( Rcs,h1). The colour rendition conditions did not meet the criterion for none, one, two or all three of these measures. Participants, who chromatically adapted to each chromaticity group, rated the objects' colour appearance on eight-point scales for saturated–dull, normal–shifted and like-dislike (preference), as well as a binary for acceptable or unacceptable. The findings corroborate past work, but also indicate that colour preference criteria could be adjusted slightly to improve performance, with Tier A having Rf ≥ 78, Rg ≥ 95 and −1% ≤ Rcs,h1 ≤ 15%, Tier B having Rf ≥ 74, Rg ≥ 92 and −7% ≤ Rcs,h1 ≤ 19%, and Tier C having Rf ≥ 70, Rg ≥ 89 and −12% ≤ Rcs,h1 ≤ 23%. A companion regression analysis shows models based on Rf, Rg and Rcs,h1 were superior in predicting colour preference compared to those using other measures of colour rendition.

Generic Preferences over Subsets of Structured Objects

Various tasks in decision making and decision support systems require selecting a preferred subset of a given set of items. Here we focus on problems where the individual items are described using a set of characterizing attributes, and a generic preference specification is required, that is, a specification that can work with an arbitrary set of items. For example, preferences over the content of an online newspaper should have this form: At each viewing, the newspaper contains a subset of the set of articles currently available. Our preference specification over this subset should be provided offline, but we should be able to use it to select a subset of any currently available set of articles, e.g., based on their tags. We present a general approach for lifting formalisms for specifying preferences over objects with multiple attributes into ones that specify preferences over subsets of such objects. We also show how we can compute an optimal subset given such a specification in a relatively efficient manner. We provide an empirical evaluation of the approach as well as some worst-case complexity results.