Grappling with movement models: performing arts and slippery contexts

The ways we leave, recognise, and interpret marks of human movement are deeply entwined with layerings of collective memory. Although we retroactively order chronological sediments to map shareable stories, our remediations often emerge unpredictably from a multidimensional mnemonic fabric: contemporary ideas can resonate with ancient aspirations and initiatives, and foreign fields of investigation can inform ostensibly unrelated endeavours. Such links reinforce the debunking of grand narratives, and resonate with quests for the new kinds of thinking needed to address the mix of living, technological, and semiotic systems that makes up our wider ecology. As a highly evolving field, movement-and-computing is exceptionally open to, and needy of, this diversity. This paper argues for awareness of the analytical apparatus we sometimes too unwittingly bring to bear on our research objects, and for the value of transdisciplinary and tangential thinking to diversify our research questions. With a view to seeking ways to articulate new, shareable questions rather than propose answers, it looks at wider questions of problem-framing. It emphasises the importance of - quite literally - grounding movement, of recognising its environmental implications and qualities. Informed by work on expressive gesture and creative use of instruments in domains including puppetry and music, this paper also insists on the complexity and heterogeneity of the research strands that are indissociably bound up in our corporeal-technological movement practices

Structured Knowledge Representation for Image Retrieval

We propose a structured approach to the problem of retrieval of images by content and present a description logic that has been devised for the semantic indexing and retrieval of images containing complex objects. As other approaches do, we start from low-level features extracted with image analysis to detect and characterize regions in an image. However, in contrast with feature-based approaches, we provide a syntax to describe segmented regions as basic objects and complex objects as compositions of basic ones. Then we introduce a companion extensional semantics for defining reasoning services, such as retrieval, classification, and subsumption. These services can be used for both exact and approximate matching, using similarity measures. Using our logical approach as a formal specification, we implemented a complete client-server image retrieval system, which allows a user to pose both queries by sketch and queries by example. A set of experiments has been carried out on a testbed of images to assess the retrieval capabilities of the system in comparison with expert users ranking. Results are presented adopting a well-established measure of quality borrowed from textual information retrieval

EstSoil-EH: a high-resolution eco-hydrological modelling parameters dataset for Estonia

https://essd.copernicus.org/articles/13/83/2021