253,409 research outputs found
Leveraging Deep Visual Descriptors for Hierarchical Efficient Localization
Many robotics applications require precise pose estimates despite operating
in large and changing environments. This can be addressed by visual
localization, using a pre-computed 3D model of the surroundings. The pose
estimation then amounts to finding correspondences between 2D keypoints in a
query image and 3D points in the model using local descriptors. However,
computational power is often limited on robotic platforms, making this task
challenging in large-scale environments. Binary feature descriptors
significantly speed up this 2D-3D matching, and have become popular in the
robotics community, but also strongly impair the robustness to perceptual
aliasing and changes in viewpoint, illumination and scene structure. In this
work, we propose to leverage recent advances in deep learning to perform an
efficient hierarchical localization. We first localize at the map level using
learned image-wide global descriptors, and subsequently estimate a precise pose
from 2D-3D matches computed in the candidate places only. This restricts the
local search and thus allows to efficiently exploit powerful non-binary
descriptors usually dismissed on resource-constrained devices. Our approach
results in state-of-the-art localization performance while running in real-time
on a popular mobile platform, enabling new prospects for robotics research.Comment: CoRL 2018 Camera-ready (fix typos and update citations
The construction of a vocabulary test for the intermediate grades,
Thesis (M.A.)--Boston Universit
Evaluation of CNN-based Single-Image Depth Estimation Methods
While an increasing interest in deep models for single-image depth estimation
methods can be observed, established schemes for their evaluation are still
limited. We propose a set of novel quality criteria, allowing for a more
detailed analysis by focusing on specific characteristics of depth maps. In
particular, we address the preservation of edges and planar regions, depth
consistency, and absolute distance accuracy. In order to employ these metrics
to evaluate and compare state-of-the-art single-image depth estimation
approaches, we provide a new high-quality RGB-D dataset. We used a DSLR camera
together with a laser scanner to acquire high-resolution images and highly
accurate depth maps. Experimental results show the validity of our proposed
evaluation protocol
'Achieving Bologna convergence: is ECTS failing to make the grade?'
Transparent and consistent credit transfer procedures are essential if EU Universities are to successfully build the European Higher Education Learning Area and thrive in the emerging global knowledge economy. Currently the European Credit Transfer System is the most widely used mechanism to enable credit transfer between universities in different EU nations. Using data from 20 universities in four EU states, this paper examines the problems of calculating and using ECTS grades. The results demonstrate that the alignment of ECTS grades varies within nation states and show that, despite the fact that ECTS grading is a norm referenced system, while the national systems are usually criterion referenced, many ECTS conversion tables provided by universities indicate straight line transference from institutional to ECTS grades . Given the anticipated increase in student mobility following the EU enlargement to 25 nations, the paper proposes a re-alignment of ECTS towards a criterion referenced system. Such a new system would acknowledge and build on the diversity of EU higher education systems, unlike the current mechanistic system, which both masks this diversity and is flawed in calculation, and ad hoc in operation
The relative value of recall and recognition techniques for measuring precise knowledge of word meaning nouns, verbs, adjectives
Thesis (Ed.D.)--Boston University. This item was digitized by the Internet Archive
An approach toward function allocation between humans and machines in space station activities
Basic guidelines and data to assist in the allocation of functions between humans and automated systems in a manned permanent space station are provided. Human capabilities and limitations are described. Criteria and guidelines for various levels of automation and human participation are described. A collection of human factors data is included
Dynamic Construction of Stimulus Values in the Ventromedial Prefrontal Cortex
Signals representing the value assigned to stimuli at the time of choice have been repeatedly observed in ventromedial prefrontal cortex (vmPFC). Yet it remains unknown how these value representations are computed from sensory and memory representations in more posterior brain regions. We used electroencephalography (EEG) while subjects evaluated appetitive and aversive food items to study how event-related responses modulated by stimulus value evolve over time. We found that value-related activity shifted from posterior to anterior, and from parietal to central to frontal sensors, across three major time windows after stimulus onset: 150–250 ms, 400–550 ms, and 700–800 ms. Exploratory localization of the EEG signal revealed a shifting network of activity moving from sensory and memory structures to areas associated with value coding, with stimulus value activity localized to vmPFC only from 400 ms onwards. Consistent with these results, functional connectivity analyses also showed a causal flow of information from temporal cortex to vmPFC. Thus, although value signals are present as early as 150 ms after stimulus onset, the value signals in vmPFC appear relatively late in the choice process, and seem to reflect the integration of incoming information from sensory and memory related regions
Historical collaborative geocoding
The latest developments in digital have provided large data sets that can
increasingly easily be accessed and used. These data sets often contain
indirect localisation information, such as historical addresses. Historical
geocoding is the process of transforming the indirect localisation information
to direct localisation that can be placed on a map, which enables spatial
analysis and cross-referencing. Many efficient geocoders exist for current
addresses, but they do not deal with the temporal aspect and are based on a
strict hierarchy (..., city, street, house number) that is hard or impossible
to use with historical data. Indeed historical data are full of uncertainties
(temporal aspect, semantic aspect, spatial precision, confidence in historical
source, ...) that can not be resolved, as there is no way to go back in time to
check. We propose an open source, open data, extensible solution for geocoding
that is based on the building of gazetteers composed of geohistorical objects
extracted from historical topographical maps. Once the gazetteers are
available, geocoding an historical address is a matter of finding the
geohistorical object in the gazetteers that is the best match to the historical
address. The matching criteriae are customisable and include several dimensions
(fuzzy semantic, fuzzy temporal, scale, spatial precision ...). As the goal is
to facilitate historical work, we also propose web-based user interfaces that
help geocode (one address or batch mode) and display over current or historical
topographical maps, so that they can be checked and collaboratively edited. The
system is tested on Paris city for the 19-20th centuries, shows high returns
rate and is fast enough to be used interactively.Comment: WORKING PAPE
Collective frames of reference, recognition, and managers' mental models of competition: a test in two industries
This work was supported by ESRC grant no. R000232883.Managers draw upon sources of collective knowledge to cognitively represent strategic
issues. It has also be argued that cognition is embedded in social interaction, enabling
managers to recognize of others’ cognitions. In two separate industries, this study found
that the influences upon managers’ mental models of their competitive environment include
industry membership, organizational membership, and management level. The results
indicate further that recognition of others’ mental models may be more pronounced than
cognitive similarity.School of Managemen
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