Foto: André Stephan
Xiaoyi Jiang, University of Münster,Germany
Biomedical Imaging: A Galisonian Perspective for Sciences
In biology and medicine imaging has become an indispensable tool for basic research and clinical practice. Many image reconstruction, processing and analysis algorithms have been developed and successfully adopted to biomedical applications. The specific characteristics of biomedical image data have. motivated researchers to develop novel concepts and algorithms. This talk emphasizes the fundamental research view of biomedical computer vision and discusses a number of related challenges, concepts, and algorithms. In addition to the information processing view the imposing development in biomedical imaging also provides a driving force for sciences from a Galisonian perspective.
Shuicheng Yan, National University of Singapore
Deep Learning towards on-device AI
To be announced.
Color Contrast in the Aesthetic Image: An examination of the complex ways that color contrast manifests in paintings
A painting is a special class of image. Its every element has been crafted by the painter with obsessive attention to how its influences its visual impact. Informing this are formalities are near-limitless complexity, formalities which address such things as colour, content, texture and composition. Martin will be addressing one small corner of this complexity-domain: colour contrast. For the last ten years he has been working with a team of engineers attempting to identify and quantify the many different forms that colour contrast takes in the aesthetic domain. The work they did was uniquely co-dependant, with the artist and the engineers working side-by-side.
Martin will begin by introducing Itten’s six colour contrasts, and the influence they have had on his work and related work by other researchers. He will then describe the six structural contrasts of painting: global contrast, local contrast, centre-corner contrast, regional contrast, neighbouring regional contrast and depth-aware contrast. Following this he will address a range of colour spaces: RGB, RYB, HSL and Munsell. These he will introduce as conceptual models: each addressing the colour experience in different ways, and each playing a different role in his research. He will conclude with an introduction to his ongoing research on global hue contrast, a topic he believes is ill-understood in the engineering domain.
With a photographic image being increasingly available to high-level manipulation, now seems a very apt time for this kind of research. What might we learn from artists? How, perhaps, might a photograph be aesthetically improved with reference to such information?