24,412 research outputs found
Visual Importance-Biased Image Synthesis Animation
Present ray tracing algorithms are computationally intensive, requiring hours of computing time for complex scenes. Our previous work has dealt with the development of an overall approach to the application of visual attention to progressive and adaptive ray-tracing techniques. The approach facilitates large computational savings by modulating the supersampling rates in an image by the visual importance of the region being rendered. This paper extends the approach by incorporating temporal changes into the models and techniques developed, as it is expected that further efficiency savings can be reaped for animated scenes. Applications for this approach include entertainment, visualisation and simulation
Quantifying and Transferring Contextual Information in Object Detection
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Hard to Cheat: A Turing Test based on Answering Questions about Images
Progress in language and image understanding by machines has sparkled the
interest of the research community in more open-ended, holistic tasks, and
refueled an old AI dream of building intelligent machines. We discuss a few
prominent challenges that characterize such holistic tasks and argue for
"question answering about images" as a particular appealing instance of such a
holistic task. In particular, we point out that it is a version of a Turing
Test that is likely to be more robust to over-interpretations and contrast it
with tasks like grounding and generation of descriptions. Finally, we discuss
tools to measure progress in this field.Comment: Presented in AAAI-15 Workshop: Beyond the Turing Tes
Continuity in cognition
Designing for continuous interaction requires
designers to consider the way in which human users can
perceive and evaluate an artefact’s observable behaviour,
in order to make inferences about its state and plan, and
execute their own continuous behaviour. Understanding
the human point of view in continuous interaction requires
an understanding of human causal reasoning, of
the way in which humans perceive and structure the
world, and of human cognition. We present a framework
for representing human cognition, and show briefly how it
relates to the analysis of structure in continuous interaction,
and the ways in which it may be applied in design
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Shape interpretation with design computing
How information is interpreted has significant impact on how it can be used. This is particularly important in design where information from a wide variety of sources is used in a wide variety of contexts and in a wide variety of ways. This paper is concerned with the information that is created, modified and analysed during design processes, specifically with the information that is represented in shapes. It investigates how design computing seeks to support these processes, and the difficulties that arise when it is necessary to consider alternative interpretations of shape. The aim is to establish the problem of shape interpretation as a general challenge for research in design computing, rather than a difficulty that is to be overcome within specific processes. Shape interpretations are common characteristics of several areas of enquiry in design computing. This paper reviews these, brings an integrated perspective and draws conclusions about how this underlying process can be supported
Weakly Supervised Learning of Objects, Attributes and Their Associations
The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-10605-2_31]”
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