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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Event-Based 3D Motion Flow Estimation Using 4D Spatio Temporal Subspaces Properties
|
|---|---|
| Published in |
Frontiers in Neuroscience, February 2017
|
| DOI | 10.3389/fnins.2016.00596 |
| Pubmed ID | |
| Authors |
Sio-Hoi Ieng, João Carneiro, Ryad B. Benosman |
| Abstract |
State of the art scene flow estimation techniques are based on projections of the 3D motion on image using luminance-sampled at the frame rate of the cameras-as the principal source of information. We introduce in this paper a pure time based approach to estimate the flow from 3D point clouds primarily output by neuromorphic event-based stereo camera rigs, or by any existing 3D depth sensor even if it does not provide nor use luminance. This method formulates the scene flow problem by applying a local piecewise regularization of the scene flow. The formulation provides a unifying framework to estimate scene flow from synchronous and asynchronous 3D point clouds. It relies on the properties of 4D space time using a decomposition into its subspaces. This method naturally exploits the properties of the neuromorphic asynchronous event based vision sensors that allows continuous time 3D point clouds reconstruction. The approach can also handle the motion of deformable object. Experiments using different 3D sensors are presented. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Canada | 1 | 25% |
| United Kingdom | 1 | 25% |
| Switzerland | 1 | 25% |
| Unknown | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 1 | 3% |
| Unknown | 35 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 6 | 17% |
| Student > Master | 6 | 17% |
| Professor | 4 | 11% |
| Researcher | 4 | 11% |
| Student > Postgraduate | 2 | 6% |
| Other | 4 | 11% |
| Unknown | 10 | 28% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 10 | 28% |
| Computer Science | 10 | 28% |
| Arts and Humanities | 1 | 3% |
| Business, Management and Accounting | 1 | 3% |
| Agricultural and Biological Sciences | 1 | 3% |
| Other | 2 | 6% |
| Unknown | 11 | 31% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 17 April 2017.
All research outputs
#15,097,241
of 25,382,440 outputs
Outputs from Frontiers in Neuroscience
#6,298
of 11,542 outputs
Outputs of similar age
#223,807
of 424,791 outputs
Outputs of similar age from Frontiers in Neuroscience
#89
of 185 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. This one is in the 40th percentile – i.e., 40% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,542 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.0. This one is in the 44th percentile – i.e., 44% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 424,791 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 185 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 50% of its contemporaries.