| Earlier this was a separate project, it is now part of Citizen Science Grid
Wildlife@Home is a joint effort between UND's Department of Computer Science and Department of Biology. The project is aimed at analyzing video gathered from various cameras recording wildlife. This will be mostly done by you as volunteers. With your observations and the classification of videos into "events" algorithms can be developed for "visual detection" to filter them. This will be useful because of the enormous amount of video data.
The nest cameras will be set up both near western North Dakota's oil fields and also within protected state lands. We hope that your participation will help us determine the impact of the oil development on the sharp-tailed grouse and other wildlife in North Dakota, as well as provide some interesting video for everyone to watch and discuss!
Currently we are observing the following (threatened) bird species: Sharp-tailed grouse, interior least tern, piping plover and the blue-winged Teal
Badges can be seen on this page
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 Wildlife@Home
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| Start |
2012
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| End |
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| Status |
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| Admin |
Travis Desell
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| Institution |
University of North Dakota
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| Country |
USA
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| Area |
Biology
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 Apps
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 Win |
Wildlife@Home Descriptor Collection (SURF) 0.03
Wildlife@Home Video Background Subtractor 0.02
EXACT Convolutional Neural Network Trainer 0.09
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 Linux |
Wildlife@Home Descriptor Collection (SURF) 0.18
Wildlife@Home Video Background Subtractor 0.02
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 Mac |
Wildlife@Home Video Background Subtractor 0.02
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 64bit |
Wildlife@Home Motion Detection 0.11/0.10 [linux/mac]
Wildlife@Home Feature Detection (SURF) 0.03/0.01 [linux/mac]
Wildlife@Home Video Background Subtractor 0.02/0.07 [win/linux/mac]
EXACT Convolutional Neural Network Trainer 0.09 [win/linux/mac]
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 PS3 |
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 ATI |
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 CUDA |
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 Intel |
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 Android |
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 RPi |
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 NCI |
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 System-Specs
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| VRAM |
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SP |
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DP |
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| RAM |
60MB
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| Runtime |
11,5h
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| HDD |
770MB
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| Traffic dl/ul |
770MB / kb
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| Deadline |
4 days
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| Checkpoints |
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