When one seeks to characterize the appearance of art paint-ings, color is the visual attribute that usually focuses most atten-tion: not only does color predominate in the reading of the pic-torial work, but it is also the attribute that we best know how to evaluate scientifically, thanks to spectrophotometers or imaging systems that have become portable and affordable, and thanks to the CIE color appearance models that allow us to convert the measured physical data into quantified visual values. However, for some modern paintings, the expression of the painter relies at least as much on gloss as on color; Pierre Soulages (1919-2022) is an exemplary case. This complicates considerably the characterization of the appearance of the paintings because the scientific definition of gloss, its link with measurable light quan-tities and the measurement of these light quantities over a whole painting are much less established than for color. This paper re-ports on the knowledge, challenges and difficulties of character-izing the gloss of painted works, by outlining the track of an im-aging system to achieve this.
Incident Command Dashboard (ICD) plays an essential role in Emergency Support Functions (ESF). They are centralized with a massive amount of live data. In this project, we explore a decentralized mobile incident commanding dashboard (MIC-D) with an improved mobile augmented reality (AR) user interface (UI) that can access and display multimodal live IoT data streams in phones, tablets, and inexpensive HUDs on the first responder’s helmets. The new platform is designed to work in the field and to share live data streams among team members. It also enables users to view the 3D LiDAR scan data on the location, live thermal video data, and vital sign data on the 3D map. We have built a virtual medical helicopter communication center and tested the launchpad on fire and remote fire extinguishing scenarios. We have also tested the wildfire prevention scenario “Cold Trailing” in the outdoor environment.
The color accuracy of an LED-based multispectral imaging strategy has been evaluated with respect to the number of spectral bands used to build a color profile and render the final image. Images were captured under select illumination conditions provided by 10-channel LED light sources. First, the imaging system was characterized in its full 10-band capacity, in which an image was captured under illumination by each of the 10 LEDs in turn, and the full set used to derive a system profile. Then, the system was characterized in increasingly reduced capacities, obtained by reducing the number of bands in two ways. In one approach, image bands were systematically removed from the full 10-band set. In the other, images were captured under illumination by groups of several of the LEDs at once. For both approaches, the system was characterized using different combinations of image bands until the optimal set, giving the highest color accuracy, was determined when a total of only 9, 8, 7, or 6 bands was used to derive the profile. The results indicate that color accuracy is nearly equivalent when rendering images based on the optimal combination of anywhere from 6 to 10 spectral bands, and is maintained at a higher level than that of conventional RGB imaging. This information is a first step toward informing the development of practical LED-based multispectral imaging strategies that make spectral image capture simpler and more efficient for heritage digitization workflows.