38,361 research outputs found
Motion in place: a case study of archaeological reconstruction using motion capture
Human movement constitutes a fundamental part of the archaeological process, and of any interpretationof a site’s usage; yet there has to date been little or no consideration of how movement observed (incontemporary situations) and inferred (in archaeological reconstruction) can be documented. This paper reports on the Motion in Place Platform project, which seeks to use motion capture hardware and data totest human responses to Virtual Reality (VR) environments and their real-world equivalents using round houses of the Southern British Iron Age which have been both modelled in 3D and reconstructed in the present day as a case study. This allows us to frame questions about the assumptions which are implicitlyhardwired into VR presentations of archaeology and cultural heritage in new ways. In the future, this will lead to new insights into how VR models can be constructed, used and transmitted
Co-Fusion: Real-time Segmentation, Tracking and Fusion of Multiple Objects
In this paper we introduce Co-Fusion, a dense SLAM system that takes a live
stream of RGB-D images as input and segments the scene into different objects
(using either motion or semantic cues) while simultaneously tracking and
reconstructing their 3D shape in real time. We use a multiple model fitting
approach where each object can move independently from the background and still
be effectively tracked and its shape fused over time using only the information
from pixels associated with that object label. Previous attempts to deal with
dynamic scenes have typically considered moving regions as outliers, and
consequently do not model their shape or track their motion over time. In
contrast, we enable the robot to maintain 3D models for each of the segmented
objects and to improve them over time through fusion. As a result, our system
can enable a robot to maintain a scene description at the object level which
has the potential to allow interactions with its working environment; even in
the case of dynamic scenes.Comment: International Conference on Robotics and Automation (ICRA) 2017,
http://visual.cs.ucl.ac.uk/pubs/cofusion,
https://github.com/martinruenz/co-fusio
A statistical analysis of multiple temperature proxies: Are reconstructions of surface temperatures over the last 1000 years reliable?
Predicting historic temperatures based on tree rings, ice cores, and other
natural proxies is a difficult endeavor. The relationship between proxies and
temperature is weak and the number of proxies is far larger than the number of
target data points. Furthermore, the data contain complex spatial and temporal
dependence structures which are not easily captured with simple models. In this
paper, we assess the reliability of such reconstructions and their statistical
significance against various null models. We find that the proxies do not
predict temperature significantly better than random series generated
independently of temperature. Furthermore, various model specifications that
perform similarly at predicting temperature produce extremely different
historical backcasts. Finally, the proxies seem unable to forecast the high
levels of and sharp run-up in temperature in the 1990s either in-sample or from
contiguous holdout blocks, thus casting doubt on their ability to predict such
phenomena if in fact they occurred several hundred years ago. We propose our
own reconstruction of Northern Hemisphere average annual land temperature over
the last millennium, assess its reliability, and compare it to those from the
climate science literature. Our model provides a similar reconstruction but has
much wider standard errors, reflecting the weak signal and large uncertainty
encountered in this setting.Comment: Published in at http://dx.doi.org/10.1214/10-AOAS398 the Annals of
Applied Statistics (http://www.imstat.org/aoas/) by the Institute of
Mathematical Statistics (http://www.imstat.org
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