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Multimedia computing systems and applications

Detecting Photorealistic Computer Graphics using Convolutional Neural Networks

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16 September 2017 - 9:30pm
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2018_icip.pdf

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[1] , "Detecting Photorealistic Computer Graphics using Convolutional Neural Networks", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2204. Accessed: Oct. 22, 2017.
@article{2204-17,
url = {http://sigport.org/2204},
author = { },
publisher = {IEEE SigPort},
title = {Detecting Photorealistic Computer Graphics using Convolutional Neural Networks},
year = {2017} }
TY - EJOUR
T1 - Detecting Photorealistic Computer Graphics using Convolutional Neural Networks
AU -
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2204
ER -
. (2017). Detecting Photorealistic Computer Graphics using Convolutional Neural Networks. IEEE SigPort. http://sigport.org/2204
, 2017. Detecting Photorealistic Computer Graphics using Convolutional Neural Networks. Available at: http://sigport.org/2204.
. (2017). "Detecting Photorealistic Computer Graphics using Convolutional Neural Networks." Web.
1. . Detecting Photorealistic Computer Graphics using Convolutional Neural Networks [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2204

PIX2NVS: Parameterized Conversion of Pixel-domain Video Streams to Neuromorphic Vision Streams

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14 September 2017 - 6:45am
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ICIP2017_2371_Yin_Slides

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[1] , "PIX2NVS: Parameterized Conversion of Pixel-domain Video Streams to Neuromorphic Vision Streams", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2012. Accessed: Oct. 22, 2017.
@article{2012-17,
url = {http://sigport.org/2012},
author = { },
publisher = {IEEE SigPort},
title = {PIX2NVS: Parameterized Conversion of Pixel-domain Video Streams to Neuromorphic Vision Streams},
year = {2017} }
TY - EJOUR
T1 - PIX2NVS: Parameterized Conversion of Pixel-domain Video Streams to Neuromorphic Vision Streams
AU -
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2012
ER -
. (2017). PIX2NVS: Parameterized Conversion of Pixel-domain Video Streams to Neuromorphic Vision Streams. IEEE SigPort. http://sigport.org/2012
, 2017. PIX2NVS: Parameterized Conversion of Pixel-domain Video Streams to Neuromorphic Vision Streams. Available at: http://sigport.org/2012.
. (2017). "PIX2NVS: Parameterized Conversion of Pixel-domain Video Streams to Neuromorphic Vision Streams." Web.
1. . PIX2NVS: Parameterized Conversion of Pixel-domain Video Streams to Neuromorphic Vision Streams [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2012

[Presentation Slide] A Novel Kinect V2 Registration Method For Large-Displacement Environments Using Camera And Scene Constraints


In a lot of multi-Kinect V2-based systems, the registration of these Kinect V2 sensors is an important step which directly affects the system precision. The coarse-to-fine method using calibration objects is an effective way to solve the Kinect V2 registration problem. However, for the registration of Kinect V2 cameras with large displacements, this kind of method may fail. To this end, a novel Kinect V2 registration method, which is also based on the coarse-to-fine framework, is proposed by using camera and scene constraints.

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Yuan Gao, Sandro Esquivel, Reinhard Koch, Matthias Ziegler, Frederik Zilly, Joachim Keinert
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21 September 2017 - 11:43pm
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2017.09.19ICIP.pdf

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[1] Yuan Gao, Sandro Esquivel, Reinhard Koch, Matthias Ziegler, Frederik Zilly, Joachim Keinert, "[Presentation Slide] A Novel Kinect V2 Registration Method For Large-Displacement Environments Using Camera And Scene Constraints", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1849. Accessed: Oct. 22, 2017.
@article{1849-17,
url = {http://sigport.org/1849},
author = {Yuan Gao; Sandro Esquivel; Reinhard Koch; Matthias Ziegler; Frederik Zilly; Joachim Keinert },
publisher = {IEEE SigPort},
title = {[Presentation Slide] A Novel Kinect V2 Registration Method For Large-Displacement Environments Using Camera And Scene Constraints},
year = {2017} }
TY - EJOUR
T1 - [Presentation Slide] A Novel Kinect V2 Registration Method For Large-Displacement Environments Using Camera And Scene Constraints
AU - Yuan Gao; Sandro Esquivel; Reinhard Koch; Matthias Ziegler; Frederik Zilly; Joachim Keinert
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1849
ER -
Yuan Gao, Sandro Esquivel, Reinhard Koch, Matthias Ziegler, Frederik Zilly, Joachim Keinert. (2017). [Presentation Slide] A Novel Kinect V2 Registration Method For Large-Displacement Environments Using Camera And Scene Constraints. IEEE SigPort. http://sigport.org/1849
Yuan Gao, Sandro Esquivel, Reinhard Koch, Matthias Ziegler, Frederik Zilly, Joachim Keinert, 2017. [Presentation Slide] A Novel Kinect V2 Registration Method For Large-Displacement Environments Using Camera And Scene Constraints. Available at: http://sigport.org/1849.
Yuan Gao, Sandro Esquivel, Reinhard Koch, Matthias Ziegler, Frederik Zilly, Joachim Keinert. (2017). "[Presentation Slide] A Novel Kinect V2 Registration Method For Large-Displacement Environments Using Camera And Scene Constraints." Web.
1. Yuan Gao, Sandro Esquivel, Reinhard Koch, Matthias Ziegler, Frederik Zilly, Joachim Keinert. [Presentation Slide] A Novel Kinect V2 Registration Method For Large-Displacement Environments Using Camera And Scene Constraints [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1849

TRACKING HIERARCHICAL STRUCTURE OF WEB VIDEO GROUPS BASED ON SALIENT KEYWORD MATCHING INCLUDING SEMANTIC BROADNESS ESTIMATION


This paper presents a novel method to track the hierarchical structure of Web video groups on the basis of salient keyword matching including semantic broadness estimation. To the best of our knowledge, this paper is the first work to perform extraction and tracking of the hierarchical structure simultaneously. Specifically, the proposed method first extracts the hierarchical structure of Web video groups and salient keywords of them on the basis of an improved scheme of our previously reported method.

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Ryosuke Harakawa,Takahiro Ogawa,Miki Haseyama
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6 December 2016 - 6:46pm
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harakawa_globalsip2016.pdf

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[1] Ryosuke Harakawa,Takahiro Ogawa,Miki Haseyama, "TRACKING HIERARCHICAL STRUCTURE OF WEB VIDEO GROUPS BASED ON SALIENT KEYWORD MATCHING INCLUDING SEMANTIC BROADNESS ESTIMATION", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1375. Accessed: Oct. 22, 2017.
@article{1375-16,
url = {http://sigport.org/1375},
author = {Ryosuke Harakawa;Takahiro Ogawa;Miki Haseyama },
publisher = {IEEE SigPort},
title = {TRACKING HIERARCHICAL STRUCTURE OF WEB VIDEO GROUPS BASED ON SALIENT KEYWORD MATCHING INCLUDING SEMANTIC BROADNESS ESTIMATION},
year = {2016} }
TY - EJOUR
T1 - TRACKING HIERARCHICAL STRUCTURE OF WEB VIDEO GROUPS BASED ON SALIENT KEYWORD MATCHING INCLUDING SEMANTIC BROADNESS ESTIMATION
AU - Ryosuke Harakawa;Takahiro Ogawa;Miki Haseyama
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1375
ER -
Ryosuke Harakawa,Takahiro Ogawa,Miki Haseyama. (2016). TRACKING HIERARCHICAL STRUCTURE OF WEB VIDEO GROUPS BASED ON SALIENT KEYWORD MATCHING INCLUDING SEMANTIC BROADNESS ESTIMATION. IEEE SigPort. http://sigport.org/1375
Ryosuke Harakawa,Takahiro Ogawa,Miki Haseyama, 2016. TRACKING HIERARCHICAL STRUCTURE OF WEB VIDEO GROUPS BASED ON SALIENT KEYWORD MATCHING INCLUDING SEMANTIC BROADNESS ESTIMATION. Available at: http://sigport.org/1375.
Ryosuke Harakawa,Takahiro Ogawa,Miki Haseyama. (2016). "TRACKING HIERARCHICAL STRUCTURE OF WEB VIDEO GROUPS BASED ON SALIENT KEYWORD MATCHING INCLUDING SEMANTIC BROADNESS ESTIMATION." Web.
1. Ryosuke Harakawa,Takahiro Ogawa,Miki Haseyama. TRACKING HIERARCHICAL STRUCTURE OF WEB VIDEO GROUPS BASED ON SALIENT KEYWORD MATCHING INCLUDING SEMANTIC BROADNESS ESTIMATION [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1375

Multimedia Content Creation using Global Network Cameras: The Making of CAM2

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Youngsol Koh, Everett Berry, Kyle McNulty, Yung-Hsiang Lu, Edward J. Delp
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23 February 2016 - 1:44pm
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slides.pdf

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[1] Youngsol Koh, Everett Berry, Kyle McNulty, Yung-Hsiang Lu, Edward J. Delp, "Multimedia Content Creation using Global Network Cameras: The Making of CAM2", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/408. Accessed: Oct. 22, 2017.
@article{408-15,
url = {http://sigport.org/408},
author = {Youngsol Koh; Everett Berry; Kyle McNulty; Yung-Hsiang Lu; Edward J. Delp },
publisher = {IEEE SigPort},
title = {Multimedia Content Creation using Global Network Cameras: The Making of CAM2},
year = {2015} }
TY - EJOUR
T1 - Multimedia Content Creation using Global Network Cameras: The Making of CAM2
AU - Youngsol Koh; Everett Berry; Kyle McNulty; Yung-Hsiang Lu; Edward J. Delp
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/408
ER -
Youngsol Koh, Everett Berry, Kyle McNulty, Yung-Hsiang Lu, Edward J. Delp. (2015). Multimedia Content Creation using Global Network Cameras: The Making of CAM2. IEEE SigPort. http://sigport.org/408
Youngsol Koh, Everett Berry, Kyle McNulty, Yung-Hsiang Lu, Edward J. Delp, 2015. Multimedia Content Creation using Global Network Cameras: The Making of CAM2. Available at: http://sigport.org/408.
Youngsol Koh, Everett Berry, Kyle McNulty, Yung-Hsiang Lu, Edward J. Delp. (2015). "Multimedia Content Creation using Global Network Cameras: The Making of CAM2." Web.
1. Youngsol Koh, Everett Berry, Kyle McNulty, Yung-Hsiang Lu, Edward J. Delp. Multimedia Content Creation using Global Network Cameras: The Making of CAM2 [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/408

Gait Analysis using a Single Depth Camera


Gait analysis is often used as part of the rehabilitation program for post-stoke recovery assessment. Since current optical diagnostic and patient assessment tools tend to be expensive and not portable, this paper proposes a novel marker-based tracking system using a single depth camera which provides a cost-effective solution suitable for home and clinic use. The proposed system can simultaneously generate motion patterns even within a complex background using the proposed geometric model-based algorithm and autonomously provide gait analysis results.

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Authors:
Minxiang Ye, Cheng Yang, Lina Stankovic, Andrew Kerr
Submitted On:
23 February 2016 - 1:44pm
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Minxiang-printed.pdf

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[1] Minxiang Ye, Cheng Yang, Lina Stankovic, Andrew Kerr, "Gait Analysis using a Single Depth Camera", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/275. Accessed: Oct. 22, 2017.
@article{275-15,
url = {http://sigport.org/275},
author = {Minxiang Ye; Cheng Yang; Lina Stankovic; Andrew Kerr },
publisher = {IEEE SigPort},
title = {Gait Analysis using a Single Depth Camera},
year = {2015} }
TY - EJOUR
T1 - Gait Analysis using a Single Depth Camera
AU - Minxiang Ye; Cheng Yang; Lina Stankovic; Andrew Kerr
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/275
ER -
Minxiang Ye, Cheng Yang, Lina Stankovic, Andrew Kerr. (2015). Gait Analysis using a Single Depth Camera. IEEE SigPort. http://sigport.org/275
Minxiang Ye, Cheng Yang, Lina Stankovic, Andrew Kerr, 2015. Gait Analysis using a Single Depth Camera. Available at: http://sigport.org/275.
Minxiang Ye, Cheng Yang, Lina Stankovic, Andrew Kerr. (2015). "Gait Analysis using a Single Depth Camera." Web.
1. Minxiang Ye, Cheng Yang, Lina Stankovic, Andrew Kerr. Gait Analysis using a Single Depth Camera [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/275