Signal Processing

TST Intake Monitoring dataset v1


The dataset contains depth frames collected using Microsoft Kinect v1 during the execution of food and drink intake movements.

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Dataset Details

Citation Author(s):
Submitted by:
Susanna Spinsante
Last updated:
Fri, 01/06/2017 - 16:19
DOI:
10.21227/H2G59T
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[1] , "TST Intake Monitoring dataset v1 ", IEEE Dataport, 2016. [Online]. Available: http://dx.doi.org/10.21227/H2G59T. Accessed: Nov. 22, 2017.
@data{h2g59t-16,
doi = {10.21227/H2G59T},
url = {http://dx.doi.org/10.21227/H2G59T},
author = { },
publisher = {IEEE Dataport},
title = {TST Intake Monitoring dataset v1 },
year = {2016} }
TY - DATA
T1 - TST Intake Monitoring dataset v1
AU -
PY - 2016
PB - IEEE Dataport
UR - 10.21227/H2G59T
ER -
. (2016). TST Intake Monitoring dataset v1 . IEEE Dataport. http://dx.doi.org/10.21227/H2G59T
, 2016. TST Intake Monitoring dataset v1 . Available at: http://dx.doi.org/10.21227/H2G59T.
. (2016). "TST Intake Monitoring dataset v1 ." Web.
1. . TST Intake Monitoring dataset v1 [Internet]. IEEE Dataport; 2016. Available from : http://dx.doi.org/10.21227/H2G59T
. "TST Intake Monitoring dataset v1 ." doi: 10.21227/H2G59T

TST TUG dataset


The dataset contains depth frames and skeleton joints collected using Microsoft Kinect v2 and acceleration samples provided by an IMU during the execution of the timed up and go test.

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Dataset Details

Citation Author(s):
Submitted by:
Susanna Spinsante
Last updated:
Fri, 01/06/2017 - 15:47
DOI:
10.21227/H2KW2B
Data Format:
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[1] , "TST TUG dataset ", IEEE Dataport, 2016. [Online]. Available: http://dx.doi.org/10.21227/H2KW2B. Accessed: Nov. 22, 2017.
@data{h2kw2b-16,
doi = {10.21227/H2KW2B},
url = {http://dx.doi.org/10.21227/H2KW2B},
author = { },
publisher = {IEEE Dataport},
title = {TST TUG dataset },
year = {2016} }
TY - DATA
T1 - TST TUG dataset
AU -
PY - 2016
PB - IEEE Dataport
UR - 10.21227/H2KW2B
ER -
. (2016). TST TUG dataset . IEEE Dataport. http://dx.doi.org/10.21227/H2KW2B
, 2016. TST TUG dataset . Available at: http://dx.doi.org/10.21227/H2KW2B.
. (2016). "TST TUG dataset ." Web.
1. . TST TUG dataset [Internet]. IEEE Dataport; 2016. Available from : http://dx.doi.org/10.21227/H2KW2B
. "TST TUG dataset ." doi: 10.21227/H2KW2B

TST Fall detection dataset v2


The dataset contains depth frames and skeleton joints collected using Microsoft Kinect v2 and acceleration samples provided by an IMU during the simulation of ADLs and falls.

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Dataset Details

Citation Author(s):
Submitted by:
Susanna Spinsante
Last updated:
Fri, 01/06/2017 - 15:26
DOI:
10.21227/H2QP48
Data Format:
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[1] , "TST Fall detection dataset v2", IEEE Dataport, 2016. [Online]. Available: http://dx.doi.org/10.21227/H2QP48. Accessed: Nov. 22, 2017.
@data{h2qp48-16,
doi = {10.21227/H2QP48},
url = {http://dx.doi.org/10.21227/H2QP48},
author = { },
publisher = {IEEE Dataport},
title = {TST Fall detection dataset v2},
year = {2016} }
TY - DATA
T1 - TST Fall detection dataset v2
AU -
PY - 2016
PB - IEEE Dataport
UR - 10.21227/H2QP48
ER -
. (2016). TST Fall detection dataset v2. IEEE Dataport. http://dx.doi.org/10.21227/H2QP48
, 2016. TST Fall detection dataset v2. Available at: http://dx.doi.org/10.21227/H2QP48.
. (2016). "TST Fall detection dataset v2." Web.
1. . TST Fall detection dataset v2 [Internet]. IEEE Dataport; 2016. Available from : http://dx.doi.org/10.21227/H2QP48
. "TST Fall detection dataset v2." doi: 10.21227/H2QP48

TST Fall detection dataset v1


The dataset contains depth frames collected using Microsoft Kinect v1 in top-view configuration and can be used for fall detection.

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Dataset Details

Citation Author(s):
Submitted by:
Susanna Spinsante
Last updated:
Fri, 01/06/2017 - 15:00
DOI:
10.21227/H2VC7J
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[1] , "TST Fall detection dataset v1", IEEE Dataport, 2016. [Online]. Available: http://dx.doi.org/10.21227/H2VC7J. Accessed: Nov. 22, 2017.
@data{h2vc7j-16,
doi = {10.21227/H2VC7J},
url = {http://dx.doi.org/10.21227/H2VC7J},
author = { },
publisher = {IEEE Dataport},
title = {TST Fall detection dataset v1},
year = {2016} }
TY - DATA
T1 - TST Fall detection dataset v1
AU -
PY - 2016
PB - IEEE Dataport
UR - 10.21227/H2VC7J
ER -
. (2016). TST Fall detection dataset v1. IEEE Dataport. http://dx.doi.org/10.21227/H2VC7J
, 2016. TST Fall detection dataset v1. Available at: http://dx.doi.org/10.21227/H2VC7J.
. (2016). "TST Fall detection dataset v1." Web.
1. . TST Fall detection dataset v1 [Internet]. IEEE Dataport; 2016. Available from : http://dx.doi.org/10.21227/H2VC7J
. "TST Fall detection dataset v1." doi: 10.21227/H2VC7J

ENF Power Frequency Data for Location Forensics (IEEE SP Cup 2016 competition)


At the intersection of signal processing and information forensics, the Signal Processing Cup 2016 global competition has explored a time-varying location-dependent signature of power grids that can be intrinsically captured in media recordings. This signature is called the Electric Network Frequency (ENF) signals. Throughout the SP Cup 2016 competition, participants were provided with multiple training, practice, and testing datasets that consisted of recordings made in different grids and containing ENF traces.

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Dataset Details

Citation Author(s):
Submitted by:
Adi Hajj-Ahmad
Last updated:
Mon, 10/24/2016 - 16:25
DOI:
10.21227/H2159S
Data Format:
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[1] , "ENF Power Frequency Data for Location Forensics (IEEE SP Cup 2016 competition)", IEEE Dataport, 2016. [Online]. Available: http://dx.doi.org/10.21227/H2159S. Accessed: Nov. 22, 2017.
@data{h2159s-16,
doi = {10.21227/H2159S},
url = {http://dx.doi.org/10.21227/H2159S},
author = { },
publisher = {IEEE Dataport},
title = {ENF Power Frequency Data for Location Forensics (IEEE SP Cup 2016 competition)},
year = {2016} }
TY - DATA
T1 - ENF Power Frequency Data for Location Forensics (IEEE SP Cup 2016 competition)
AU -
PY - 2016
PB - IEEE Dataport
UR - 10.21227/H2159S
ER -
. (2016). ENF Power Frequency Data for Location Forensics (IEEE SP Cup 2016 competition). IEEE Dataport. http://dx.doi.org/10.21227/H2159S
, 2016. ENF Power Frequency Data for Location Forensics (IEEE SP Cup 2016 competition). Available at: http://dx.doi.org/10.21227/H2159S.
. (2016). "ENF Power Frequency Data for Location Forensics (IEEE SP Cup 2016 competition)." Web.
1. . ENF Power Frequency Data for Location Forensics (IEEE SP Cup 2016 competition) [Internet]. IEEE Dataport; 2016. Available from : http://dx.doi.org/10.21227/H2159S
. "ENF Power Frequency Data for Location Forensics (IEEE SP Cup 2016 competition)." doi: 10.21227/H2159S

The Ace Challenge 2015


Several established parameters and metrics have been used to characterize the acoustics of a room. The most important are the Direct-To-Reverberant Ratio (DRR), the Reverberation Time (T60) and the reflection coefficient. The acoustic characteristics of a room based on such parameters can be used to predict the quality and intelligibility of speech signals in that room.

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Dataset Details

Citation Author(s):
Submitted by:
Alex Outman
Last updated:
Thu, 07/28/2016 - 11:35
DOI:
10.5072/FK2NV9G85X
Data Format:
Links:
 
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[1] , "The Ace Challenge 2015", IEEE Dataport, 2016. [Online]. Available: http://dx.doi.org/10.5072/FK2NV9G85X. Accessed: Nov. 22, 2017.
@data{fk2nv9g85x-16,
doi = {10.5072/FK2NV9G85X},
url = {http://dx.doi.org/10.5072/FK2NV9G85X},
author = { },
publisher = {IEEE Dataport},
title = {The Ace Challenge 2015},
year = {2016} }
TY - DATA
T1 - The Ace Challenge 2015
AU -
PY - 2016
PB - IEEE Dataport
UR - 10.5072/FK2NV9G85X
ER -
. (2016). The Ace Challenge 2015. IEEE Dataport. http://dx.doi.org/10.5072/FK2NV9G85X
, 2016. The Ace Challenge 2015. Available at: http://dx.doi.org/10.5072/FK2NV9G85X.
. (2016). "The Ace Challenge 2015." Web.
1. . The Ace Challenge 2015 [Internet]. IEEE Dataport; 2016. Available from : http://dx.doi.org/10.5072/FK2NV9G85X
. "The Ace Challenge 2015." doi: 10.5072/FK2NV9G85X

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