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Recognizing Facial Expressions in Image Sequences Using Local Parameterized Models of Image Motion

Overview of attention for article published in International Journal of Computer Vision, October 1997
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Mentioned by

patent
2 patents

Citations

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338 Dimensions

Readers on

mendeley
132 Mendeley
Title
Recognizing Facial Expressions in Image Sequences Using Local Parameterized Models of Image Motion
Published in
International Journal of Computer Vision, October 1997
DOI 10.1023/a:1007977618277
Authors

Michael J. Black, Yaser Yacoob

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 132 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 4%
Australia 2 2%
Germany 1 <1%
United Kingdom 1 <1%
Canada 1 <1%
Pakistan 1 <1%
Russia 1 <1%
Malta 1 <1%
Spain 1 <1%
Other 1 <1%
Unknown 117 89%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 49 37%
Student > Master 19 14%
Researcher 13 10%
Student > Doctoral Student 10 8%
Student > Bachelor 10 8%
Other 20 15%
Unknown 11 8%
Readers by discipline Count As %
Computer Science 63 48%
Engineering 20 15%
Psychology 13 10%
Agricultural and Biological Sciences 5 4%
Social Sciences 4 3%
Other 9 7%
Unknown 18 14%
Attention Score in Context

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 15 March 2018.
All research outputs
#8,535,472
of 25,374,647 outputs
Outputs from International Journal of Computer Vision
#458
of 1,420 outputs
Outputs of similar age
#9,366
of 28,973 outputs
Outputs of similar age from International Journal of Computer Vision
#5
of 7 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,420 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one is in the 38th percentile – i.e., 38% 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 28,973 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 9th percentile – i.e., 9% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.