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Multimedia Signal Processing

Discriminant Correlation Analysis for Feature Level Fusion with Application to Multimodal Biometrics


Discriminant Correlation Analysis for Feature Level Fusion with Application to Multimodal Biometrics

In this paper, we present Discriminant Correlation Analysis (DCA), a feature level fusion technique that incorporates the class associations in correlation analysis of the feature sets. DCA performs an effective feature fusion by maximizing the pair-wise correlations across the two feature sets, and at the same time, eliminating the between-class correlations and restricting the correlations to be within classes.

[1] Mohammad Haghighat, Mohamed Abdel-Mottaleb, Wadee Alhalabi, "Discriminant Correlation Analysis for Feature Level Fusion with Application to Multimodal Biometrics", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/828. Accessed: Nov. 17, 2018.
@article{828-16,
url = {http://sigport.org/828},
author = {Mohammad Haghighat; Mohamed Abdel-Mottaleb; Wadee Alhalabi },
publisher = {IEEE SigPort},
title = {Discriminant Correlation Analysis for Feature Level Fusion with Application to Multimodal Biometrics},
year = {2016} }
TY - EJOUR
T1 - Discriminant Correlation Analysis for Feature Level Fusion with Application to Multimodal Biometrics
AU - Mohammad Haghighat; Mohamed Abdel-Mottaleb; Wadee Alhalabi
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/828
ER -
Mohammad Haghighat, Mohamed Abdel-Mottaleb, Wadee Alhalabi. (2016). Discriminant Correlation Analysis for Feature Level Fusion with Application to Multimodal Biometrics. IEEE SigPort. http://sigport.org/828
Mohammad Haghighat, Mohamed Abdel-Mottaleb, Wadee Alhalabi, 2016. Discriminant Correlation Analysis for Feature Level Fusion with Application to Multimodal Biometrics. Available at: http://sigport.org/828.
Mohammad Haghighat, Mohamed Abdel-Mottaleb, Wadee Alhalabi. (2016). "Discriminant Correlation Analysis for Feature Level Fusion with Application to Multimodal Biometrics." Web.
1. Mohammad Haghighat, Mohamed Abdel-Mottaleb, Wadee Alhalabi. Discriminant Correlation Analysis for Feature Level Fusion with Application to Multimodal Biometrics [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/828

Audio-Based Multimedia Event Detection Using Deep Recurrent Neural Networks


Multimedia event detection (MED) is the task of detecting given events (e.g. birthday party, making a sandwich) in a large collection of video clips. While visual features and automatic speech recognition typically provide the best features for this task, non-speech audio can also contribute useful information, such as crowds cheering, engine noises, or animal sounds.

Paper Details

Authors:
Yun Wang, Leonardo Neves, Florian Metze
Submitted On:
17 March 2016 - 4:13pm
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2016.03 For ICASSP.ppt

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[1] Yun Wang, Leonardo Neves, Florian Metze, "Audio-Based Multimedia Event Detection Using Deep Recurrent Neural Networks", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/753. Accessed: Nov. 17, 2018.
@article{753-16,
url = {http://sigport.org/753},
author = {Yun Wang; Leonardo Neves; Florian Metze },
publisher = {IEEE SigPort},
title = {Audio-Based Multimedia Event Detection Using Deep Recurrent Neural Networks},
year = {2016} }
TY - EJOUR
T1 - Audio-Based Multimedia Event Detection Using Deep Recurrent Neural Networks
AU - Yun Wang; Leonardo Neves; Florian Metze
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/753
ER -
Yun Wang, Leonardo Neves, Florian Metze. (2016). Audio-Based Multimedia Event Detection Using Deep Recurrent Neural Networks. IEEE SigPort. http://sigport.org/753
Yun Wang, Leonardo Neves, Florian Metze, 2016. Audio-Based Multimedia Event Detection Using Deep Recurrent Neural Networks. Available at: http://sigport.org/753.
Yun Wang, Leonardo Neves, Florian Metze. (2016). "Audio-Based Multimedia Event Detection Using Deep Recurrent Neural Networks." Web.
1. Yun Wang, Leonardo Neves, Florian Metze. Audio-Based Multimedia Event Detection Using Deep Recurrent Neural Networks [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/753

Audio-Based Multimedia Event Detection Using Deep Recurrent Neural Networks


Multimedia event detection (MED) is the task of detecting given events (e.g. birthday party, making a sandwich) in a large collection of video clips. While visual features and automatic speech recognition typically provide the best features for this task, non-speech audio can also contribute useful information, such as crowds cheering, engine noises, or animal sounds.

Paper Details

Authors:
Yun Wang, Leonardo Neves, Florian Metze
Submitted On:
17 March 2016 - 4:13pm
Short Link:
Type:
Event:
Presenter's Name:
Document Year:
Cite

Document Files

2016.03 For ICASSP.ppt

(352 downloads)

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[1] Yun Wang, Leonardo Neves, Florian Metze, "Audio-Based Multimedia Event Detection Using Deep Recurrent Neural Networks", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/751. Accessed: Nov. 17, 2018.
@article{751-16,
url = {http://sigport.org/751},
author = {Yun Wang; Leonardo Neves; Florian Metze },
publisher = {IEEE SigPort},
title = {Audio-Based Multimedia Event Detection Using Deep Recurrent Neural Networks},
year = {2016} }
TY - EJOUR
T1 - Audio-Based Multimedia Event Detection Using Deep Recurrent Neural Networks
AU - Yun Wang; Leonardo Neves; Florian Metze
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/751
ER -
Yun Wang, Leonardo Neves, Florian Metze. (2016). Audio-Based Multimedia Event Detection Using Deep Recurrent Neural Networks. IEEE SigPort. http://sigport.org/751
Yun Wang, Leonardo Neves, Florian Metze, 2016. Audio-Based Multimedia Event Detection Using Deep Recurrent Neural Networks. Available at: http://sigport.org/751.
Yun Wang, Leonardo Neves, Florian Metze. (2016). "Audio-Based Multimedia Event Detection Using Deep Recurrent Neural Networks." Web.
1. Yun Wang, Leonardo Neves, Florian Metze. Audio-Based Multimedia Event Detection Using Deep Recurrent Neural Networks [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/751

A Finite Field Cosine Transform-Based Image Processing Scheme for Color Image Encryption

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Authors:
Edmar S. da Silva, Ricardo M. Campello de Souza
Submitted On:
23 February 2016 - 1:44pm
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presentation.pdf

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[1] Edmar S. da Silva, Ricardo M. Campello de Souza, "A Finite Field Cosine Transform-Based Image Processing Scheme for Color Image Encryption", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/337. Accessed: Nov. 17, 2018.
@article{337-15,
url = {http://sigport.org/337},
author = {Edmar S. da Silva; Ricardo M. Campello de Souza },
publisher = {IEEE SigPort},
title = {A Finite Field Cosine Transform-Based Image Processing Scheme for Color Image Encryption},
year = {2015} }
TY - EJOUR
T1 - A Finite Field Cosine Transform-Based Image Processing Scheme for Color Image Encryption
AU - Edmar S. da Silva; Ricardo M. Campello de Souza
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/337
ER -
Edmar S. da Silva, Ricardo M. Campello de Souza. (2015). A Finite Field Cosine Transform-Based Image Processing Scheme for Color Image Encryption. IEEE SigPort. http://sigport.org/337
Edmar S. da Silva, Ricardo M. Campello de Souza, 2015. A Finite Field Cosine Transform-Based Image Processing Scheme for Color Image Encryption. Available at: http://sigport.org/337.
Edmar S. da Silva, Ricardo M. Campello de Souza. (2015). "A Finite Field Cosine Transform-Based Image Processing Scheme for Color Image Encryption." Web.
1. Edmar S. da Silva, Ricardo M. Campello de Souza. A Finite Field Cosine Transform-Based Image Processing Scheme for Color Image Encryption [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/337

Brief Introduction to Image Compression - Lecture Slides


Papers

Lecture notes @ Univ. Maryland
for ENEE408G Capstone Design: Multimedia Signal Processing

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Submitted On:
23 February 2016 - 1:43pm
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Type:

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408S12_lec3_imgcode.pdf

(543 downloads)

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[1] , "Brief Introduction to Image Compression - Lecture Slides", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/134. Accessed: Nov. 17, 2018.
@article{134-15,
url = {http://sigport.org/134},
author = { },
publisher = {IEEE SigPort},
title = {Brief Introduction to Image Compression - Lecture Slides},
year = {2015} }
TY - EJOUR
T1 - Brief Introduction to Image Compression - Lecture Slides
AU -
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/134
ER -
. (2015). Brief Introduction to Image Compression - Lecture Slides. IEEE SigPort. http://sigport.org/134
, 2015. Brief Introduction to Image Compression - Lecture Slides. Available at: http://sigport.org/134.
. (2015). "Brief Introduction to Image Compression - Lecture Slides." Web.
1. . Brief Introduction to Image Compression - Lecture Slides [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/134

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