Suchergebnisse

Visual attention retargeting attempts to modify an image such that the viewer's attention is directed to specific regions. Goals include highlighting a particular object or hiding possible problems in the image. In this work, we show that we can pose the visual retargeting problem in terms of gamut mapping. In short, visual attention retargeting can be achieved by performing gamut extension in those regions that we want to highlight and gamut reduction in the other regions. ; Authors are supported by the European Research Council, Starting Grant ref. 306337, by the Spanish government FEDER Fund, grant ref. TIN2015-71537-P(MINECO/FEDER,UE), and by the Icrea Academia Award. The work of J. Vazquez-Corral was supported by the Spanish government under Grant IJCI-2014- 19516.

Gamut mapping transforms the color gamut of an image to that of a target device. Two cases are usually considered: gamut reduction (target gamut smaller than source gamut), and gamut extension (target gamut larger than the source gamut). Less attention is devoted to the more general case, when neither gamut is fully included in the other. In this work we unify and expand two recent methods for gamut extension and reduction, so as to simultaneously perform both forms of gamut mapping in di erent regions of the same image without introducing color artifacts or halos. We demonstrate the usefulness of this approach for the traditional gamut mapping problem, and also how the proposed method can be used to adapt the color palette of an image so that it is closer to that of a given reference image. Results are compared with the state-of-the-art and validated through user tests and objective metrics. ; This work is supported by the European Research Council, Starting Grant ref. 306337, by the Spanish government FEDER Fund, grant ref. TIN2015-71537-P(MINECO/FEDER,UE), and by the Icrea Academia Award. The work of J. Vazquez-Corral was supported by the Spanish government under Grant IJCI-2014-19516

Gamut mapping is the problem of transforming the colors of image or video content so as to fully exploit the color palette ofthe display device where the content will be shown, while preserving the artistic intent of the original content's creator. In particular in thecinema industry, the rapid advancement in display technologies has created a pressing need to develop automatic and fast gamutmapping algorithms. In this paper we propose a novel framework that is based on vision science models, performs both gamut reductionand gamut extension, is of low computational complexity, produces results that are free from artifacts and outperforms state-of-the-artmethods according to psychophysical tests. Our experiments also highlight the limitations of existing objective metrics for the gamutmapping problem. ; Thiswork has received funding from the European Union'sHorizon 2020 research and innovation programme undergrant agreement number 761544 (project HDR4EU) andunder grant agreement number 780470 (project SAUCE),and by the Spanish government and FEDER Fund, grantref. TIN2015-71537-P (MINECO/FEDER,UE). The work of J.Vazquez-Corral was supported by the Spanish governmentunder Grant IJCI-2014-19516

This work was supported by the European Research Council, Starting Grant ref. 306337, by the Spanish government and FEDER Fund, grant ref. TIN2015-71537-P (MINECO/FEDER,UE), and by the Icrea Academia Award. The work of Javier Vazquez-Corral was supported by the Spanish government grant IJCI-2014-19516.

Comunicació presentada a la AIC 2015 Tokyo Midterm Meeting, celebrada a Tòquio (Japó) del 19 a 22 de maig de 2015. ; Gamut mapping transforms the color of an input image within the range of a target device. A huge amount of research has been devoted to two subproblems that arise from this general one: gamut reduction and gamut extension. Gamut reduction algorithms convert the input image to a new gamut that fits inside the one of the image , i.e. the gamuts' intersection is equal to the target gamut, while gamut extension algorithms convert the input image to a gamut that embodies the original image gamut, i.e. the gamuts' intersection is equal to the source gamut. In contrast to the two aforementioned cases, very little attention has been paid to the most general problem, where the intersection of source and target gamut is not equal to one of the two gamuts. In this paper we address this most general problem of gamut mapping between any two gamuts presenting any possible intersection. To deal with this problem we unify the gamut extension and gamut reduction algorithms presented in Zamir –et al- (Zamir 2014), which are based in the perceptually inspired variational framework of Bertalmío –et al- (Bertalmío 2007) that presents three competing terms; an attachment to the original data, a term for not-modifying the perchannel image mean (i.e. not modifying the white point), and a contrast enhancement term. In particular, in this paper we show how by defining a smooth transition on the contrast enhancement parameter over the chromaticity diagram we can simultaneously reduce the input gamut in some chromatic areas while increasing it in some other without introducing neither color artifacts nor halos. ; This work was supported by the European Research Council, Starting Grant ref.306337, by the Spanish Government, grant red.TIN2012-38112, and by the Icrea Academia Award.

Comunicació presentada a: SMPTE 2016 Annual Technical Conference and Exhibition, celebrada a Los Angeles, Estats Units d'Amèrica, del 25 al 27 d'octubre de 2016. ; While wide color gamut (WCG) capabilities are a key element of emerging display and projection technologies, at present most image content is recorded using standards such as DCI-P3 for cinema or BT.709 for TV that have a reduced color gamut. Therefore, there is a need for gamut extension methods that process regular content and allow to appreciate the full color potential of new displays, improving user experience. We present a gamut extension algorithm that is based on visual perception models and explicitly takes into account low chromatic colors such as skin tones. It produces results that look natural, are free of artifacts of any kind, and outperform the state of the art. The method is fast, allowing for operation interaction if needed. ; This work was supported by the European Research Council, Starting Grant ref. 306337, by the Spanish government and FEDER Fund, grant ref. TIN2015-71537-P (MINECO/FEDER,UE), and by the Icrea Academia Award.

Comunicació presentada a: SMPTE 2017 Annual Technical Conference and Exhibition, celebrat del 23 al 26 d'octubre de 2017 a Los Angeles, Estats Units d'Amèrica. ; Gamut mapping transforms colors of the original (image or video) content to the color palette of the display device with the simultaneous goals of (a) reproducing content accurately while preserving the artistic intent of the original content's creator and (b) exploiting the full color rendering potential of the target display device. The rapid advancement in display technologies has created a pressing need to develop automatic and fast gamut mapping algorithms that can deal with imagery intended for both conventional and emerging displays. In this paper, we propose a novel framework based on retinal and color perception models from vision science that offers a functionality to perform both gamut reduction and gamut extension, while preserving hue and taking into account the analysis of the colors of the input image. We evaluate the performance of the proposed framework visually and by using a perceptually-based error metric, according to which the gamut-mapped results of our framework outperform those of the state-of-the-art methods. ; This work was supported by the European Research Council, Starting Grant ref. 306337, by the Spanish government and FEDER Fund, grant ref. TIN2015-71537-P (MINECO/FEDER,UE), and by the Icrea Academia Award. The work of Javier Vazquez-Corral was supported by the Spanish government grant IJCI-2014-19516.

Employee engagement is undeniably a crucial focus point for organisations in the twenty-first century, with motivation comprising the often missing, but vital, component of the developmental mix. Mapping Motivation for Engagement advocates a new paradigm for the twenty-first century: away from hierarchies and command-and-control management styles, towards a bottom-up approach in which the needs and motivators of the employees take centre stage. Co-written with Steve Jones, this is the third in a series of books that are all linked to the author James Sale's Motivational Map diagnostic tool. Each book builds on a different aspect of personal, team and organisational development. This book is a practical guide to the complexities of understanding and dealing with engagement in modern organisational life. Along with clear diagrams, reflective points, activities and a comprehensive index, the book provides free access to the online Motivational Map tool to facilitate a greater understanding of the contents. Drawing on copious amounts of the latest research, as well as models like the Macleod Report for the UK government, this book shows how Mapping Motivation can play a significant and crucial role in making engagement a reality, instead of a dream. Mapping Motivation for Engagement is a stimulating and thought-provoking read for a wide audience including, but not limited to, trainers and coaches working in management and motivation, experts in human resources, internal learning and development and organisational development as well as change and engagement consultants and specialists.

Time Layered Cultural Map (TLCMap) is an ambitious, ARC funded, digital humanities mapping infrastructure initiative in Australia. TLCMap infrastructure is for everyone, but the inspiration, conception and development of it has always had Aboriginal and Torres Strait Islander mapping at its heart. If Australian culture is world famous for anything it is the world���s oldest living culture, a culture for which connection to country is of vital importance. Many years ago, when a simple desire took shape to make it possible for people to add cultural layers to maps that other people could find, it was unthinkable without first considering Aboriginal and Torres Strait Islander culture and mapping technology, 'learning from' rather than 'learning about'. Indigenous views on country and its representation have factored into the software architecture and vision from the beginning. Aileen Moreton-Robinson describes indigenous and colonizing cultures as ���incommensurable'. While no translation is perfect, iconic art works such as Clifford Possum Tjapaltjarri's Warlugolong demonstrate how indigenous ontologies and ethics can be translated across cultures. Reading maps, we start learning to read the multilayered intersecting meanings of ���country��� itself, enhancing our ethical relationships to places. The transformational effect that the Colonial Frontier Massacres project has had on Australian culture was a catalyst sparking recognition of the important role digital humanities maps can play in the lives of Australians and played a role in the truth telling process of reconciliation. Five of the main projects in TLCMap are focused on Aboriginal and Torres Strait Islander culture and both acknowledge history and celebrate living culture. These projects come to TLCMap already as collaborations with Aboriginal and Torres Strait Islander people, and indigenous Australians are employed in TLCMap software development and research.