Sorry, you need to enable JavaScript to visit this website.

Image, Video, and Multidimensional Signal Processing

4D Effect Classification by Encoding CNN Features

Thomhert Siadari

4D effects are physical effects simulated in sync with videos, movies, and games to augment the events occurring in a story or a virtual world. Types of 4D effects commonly used for the immersive media may include seat motion, vibration, flash, wind, water, scent, thunderstorm, snow, and fog. Currently, the recognition of physical effects from a video is mainly conducted by human experts. Although 4D effects are promising in giving immersive experience and entertainment, this manual production has been the main obstacle to faster and wider application of 4D effects.

Paper Details

Authors:
Thomhert Siadari
Thomhert S. Siadari, Mikyong Han, Hyunjin Yoon
Submitted On:
14 September 2017 - 3:13am
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

presentation slides

(268)

Keywords

Subscribe

Send Author a Private Message
[1] Thomhert S. Siadari, Mikyong Han, Hyunjin Yoon, "4D Effect Classification by Encoding CNN Features", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1892. Accessed: May. 21, 2019.
@article{1892-17,
url = {http://sigport.org/1892},
author = {Thomhert S. Siadari; Mikyong Han; Hyunjin Yoon },
publisher = {IEEE SigPort},
title = {4D Effect Classification by Encoding CNN Features},
year = {2017} }
TY - EJOUR
T1 - 4D Effect Classification by Encoding CNN Features
AU - Thomhert S. Siadari; Mikyong Han; Hyunjin Yoon
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1892
ER -
Thomhert S. Siadari, Mikyong Han, Hyunjin Yoon. (2017). 4D Effect Classification by Encoding CNN Features. IEEE SigPort. http://sigport.org/1892
Thomhert S. Siadari, Mikyong Han, Hyunjin Yoon, 2017. 4D Effect Classification by Encoding CNN Features. Available at: http://sigport.org/1892.
Thomhert S. Siadari, Mikyong Han, Hyunjin Yoon. (2017). "4D Effect Classification by Encoding CNN Features." Web.
1. Thomhert S. Siadari, Mikyong Han, Hyunjin Yoon. 4D Effect Classification by Encoding CNN Features [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1892

SAR Image Despeckling by Combination of Fractional-Order Total Variation and Nonlocal Low Rank Regularization

Gao Chen

This paper proposes a combinational regularization model for synthetic aperture radar (SAR) image despeckling. In contrast to most of the well-known regularization methods that only use one image prior property, the proposed combinational regularization model includes both fractional-order total variation (FrTV) regularization term and nonlocal low rank (NLR) regularization term.

Paper Details

Authors:
Gao Chen
Submitted On:
10 September 2017 - 9:34pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

ICIP2017-GaoChen.pdf

(229)

Keywords

Subscribe

Send Author a Private Message
[1] , "SAR Image Despeckling by Combination of Fractional-Order Total Variation and Nonlocal Low Rank Regularization ", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1890. Accessed: May. 21, 2019.
@article{1890-17,
url = {http://sigport.org/1890},
author = { },
publisher = {IEEE SigPort},
title = {SAR Image Despeckling by Combination of Fractional-Order Total Variation and Nonlocal Low Rank Regularization },
year = {2017} }
TY - EJOUR
T1 - SAR Image Despeckling by Combination of Fractional-Order Total Variation and Nonlocal Low Rank Regularization
AU -
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1890
ER -
. (2017). SAR Image Despeckling by Combination of Fractional-Order Total Variation and Nonlocal Low Rank Regularization . IEEE SigPort. http://sigport.org/1890
, 2017. SAR Image Despeckling by Combination of Fractional-Order Total Variation and Nonlocal Low Rank Regularization . Available at: http://sigport.org/1890.
. (2017). "SAR Image Despeckling by Combination of Fractional-Order Total Variation and Nonlocal Low Rank Regularization ." Web.
1. . SAR Image Despeckling by Combination of Fractional-Order Total Variation and Nonlocal Low Rank Regularization [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1890

ByNet-SR: Image Super Resolution with a Bypass Connection Network

Jiu XU

Paper Details

Authors:
Jiu XU
Submitted On:
8 September 2017 - 9:13am
Short Link:
Type:
Event:
Presenter's Name:
Document Year:
Cite

Document Files

ICIP17-poster.pdf

(365)

Keywords

Subscribe

Send Author a Private Message
[1] , "ByNet-SR: Image Super Resolution with a Bypass Connection Network", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1876. Accessed: May. 21, 2019.
@article{1876-17,
url = {http://sigport.org/1876},
author = { },
publisher = {IEEE SigPort},
title = {ByNet-SR: Image Super Resolution with a Bypass Connection Network},
year = {2017} }
TY - EJOUR
T1 - ByNet-SR: Image Super Resolution with a Bypass Connection Network
AU -
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1876
ER -
. (2017). ByNet-SR: Image Super Resolution with a Bypass Connection Network. IEEE SigPort. http://sigport.org/1876
, 2017. ByNet-SR: Image Super Resolution with a Bypass Connection Network. Available at: http://sigport.org/1876.
. (2017). "ByNet-SR: Image Super Resolution with a Bypass Connection Network." Web.
1. . ByNet-SR: Image Super Resolution with a Bypass Connection Network [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1876

Inter-Camera Tracking Based On Fully Unsupervised Online Learning

Zheng Tang

In this paper, we present a novel fully automatic approach to track the same human across multiple disjoint cameras. Our framework includes a two-phase feature extractor and an online-learning-based camera link model estimation. We introduce an effective and robust integration of appearance and context features. Couples are detected automatically, and the couple feature is also integrated with appearance features effectively. The proposed algorithm is scalable with the use of a fully unsupervised online learning framework.

Paper Details

Authors:
Zheng Tang
Young-Gun Lee, Zheng Tang, Jenq-Neng Hwang, Zhijun Fang
Submitted On:
8 September 2017 - 3:10am
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

poster_2.pdf

(222)

Keywords

Subscribe

Send Author a Private Message
[1] Young-Gun Lee, Zheng Tang, Jenq-Neng Hwang, Zhijun Fang, "Inter-Camera Tracking Based On Fully Unsupervised Online Learning", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1869. Accessed: May. 21, 2019.
@article{1869-17,
url = {http://sigport.org/1869},
author = {Young-Gun Lee; Zheng Tang; Jenq-Neng Hwang; Zhijun Fang },
publisher = {IEEE SigPort},
title = {Inter-Camera Tracking Based On Fully Unsupervised Online Learning},
year = {2017} }
TY - EJOUR
T1 - Inter-Camera Tracking Based On Fully Unsupervised Online Learning
AU - Young-Gun Lee; Zheng Tang; Jenq-Neng Hwang; Zhijun Fang
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1869
ER -
Young-Gun Lee, Zheng Tang, Jenq-Neng Hwang, Zhijun Fang. (2017). Inter-Camera Tracking Based On Fully Unsupervised Online Learning. IEEE SigPort. http://sigport.org/1869
Young-Gun Lee, Zheng Tang, Jenq-Neng Hwang, Zhijun Fang, 2017. Inter-Camera Tracking Based On Fully Unsupervised Online Learning. Available at: http://sigport.org/1869.
Young-Gun Lee, Zheng Tang, Jenq-Neng Hwang, Zhijun Fang. (2017). "Inter-Camera Tracking Based On Fully Unsupervised Online Learning." Web.
1. Young-Gun Lee, Zheng Tang, Jenq-Neng Hwang, Zhijun Fang. Inter-Camera Tracking Based On Fully Unsupervised Online Learning [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1869

Prostate detection and segmentation based on convolutional neural network and topological derivative

ChoongSang Cho

The topological derivative (TD) for shape analysis has been employed
in image segmentation, and machine learning schemes based on
convolutional neural network (CNN) provide the high performance in
the image processing. The supervised and unsupervised approaches
have different roles and advantages according to their concepts. To
maximize the benefits of two approaches, we propose CNN-TD based
segmentation approach. A CNN-based segmentation scheme is employed
to faithfully consider the characteristics of an object to be

Paper Details

Authors:
ChoongSang Cho
Young Han Lee, Sangkeun Lee
Submitted On:
3 September 2017 - 9:24pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

20170918-ICIP-TD-DL segmentation_Cho.pdf

(12)

Keywords

Subscribe

Send Author a Private Message
[1] Young Han Lee, Sangkeun Lee, "Prostate detection and segmentation based on convolutional neural network and topological derivative", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1823. Accessed: May. 21, 2019.
@article{1823-17,
url = {http://sigport.org/1823},
author = {Young Han Lee; Sangkeun Lee },
publisher = {IEEE SigPort},
title = {Prostate detection and segmentation based on convolutional neural network and topological derivative},
year = {2017} }
TY - EJOUR
T1 - Prostate detection and segmentation based on convolutional neural network and topological derivative
AU - Young Han Lee; Sangkeun Lee
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1823
ER -
Young Han Lee, Sangkeun Lee. (2017). Prostate detection and segmentation based on convolutional neural network and topological derivative. IEEE SigPort. http://sigport.org/1823
Young Han Lee, Sangkeun Lee, 2017. Prostate detection and segmentation based on convolutional neural network and topological derivative. Available at: http://sigport.org/1823.
Young Han Lee, Sangkeun Lee. (2017). "Prostate detection and segmentation based on convolutional neural network and topological derivative." Web.
1. Young Han Lee, Sangkeun Lee. Prostate detection and segmentation based on convolutional neural network and topological derivative [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1823

Dual-Fisheye Lens Stiching for 360-Degree Imaging

Tuan Ho

Paper Details

Authors:
Tuan Ho
Tuan Ho, Madhukar Budagavi
Submitted On:
11 March 2017 - 8:41pm
Short Link:
Type:
Event:
Presenter's Name:
Document Year:
Cite

Document Files

ICASSP_POSTER_2017_Tuan.pdf

(315)

Keywords

Subscribe

Send Author a Private Message
[1] Tuan Ho, Madhukar Budagavi, "Dual-Fisheye Lens Stiching for 360-Degree Imaging", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1745. Accessed: May. 21, 2019.
@article{1745-17,
url = {http://sigport.org/1745},
author = {Tuan Ho; Madhukar Budagavi },
publisher = {IEEE SigPort},
title = {Dual-Fisheye Lens Stiching for 360-Degree Imaging},
year = {2017} }
TY - EJOUR
T1 - Dual-Fisheye Lens Stiching for 360-Degree Imaging
AU - Tuan Ho; Madhukar Budagavi
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1745
ER -
Tuan Ho, Madhukar Budagavi. (2017). Dual-Fisheye Lens Stiching for 360-Degree Imaging. IEEE SigPort. http://sigport.org/1745
Tuan Ho, Madhukar Budagavi, 2017. Dual-Fisheye Lens Stiching for 360-Degree Imaging. Available at: http://sigport.org/1745.
Tuan Ho, Madhukar Budagavi. (2017). "Dual-Fisheye Lens Stiching for 360-Degree Imaging." Web.
1. Tuan Ho, Madhukar Budagavi. Dual-Fisheye Lens Stiching for 360-Degree Imaging [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1745

STOCHASTIC TRUNCATED WIRTINGER FLOW ALGORITHM FOR PHASE RETRIEVAL USING BOOLEAN CODED APERTURES

samuel pinilla

Paper Details

Authors:
samuel pinilla
samuel pinilla, camilo noriega, henry arguello
Submitted On:
11 March 2017 - 8:46pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

main.pdf

(327)

Keywords

Subscribe

Send Author a Private Message
[1] samuel pinilla, camilo noriega, henry arguello, "STOCHASTIC TRUNCATED WIRTINGER FLOW ALGORITHM FOR PHASE RETRIEVAL USING BOOLEAN CODED APERTURES", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1718. Accessed: May. 21, 2019.
@article{1718-17,
url = {http://sigport.org/1718},
author = {samuel pinilla; camilo noriega; henry arguello },
publisher = {IEEE SigPort},
title = {STOCHASTIC TRUNCATED WIRTINGER FLOW ALGORITHM FOR PHASE RETRIEVAL USING BOOLEAN CODED APERTURES},
year = {2017} }
TY - EJOUR
T1 - STOCHASTIC TRUNCATED WIRTINGER FLOW ALGORITHM FOR PHASE RETRIEVAL USING BOOLEAN CODED APERTURES
AU - samuel pinilla; camilo noriega; henry arguello
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1718
ER -
samuel pinilla, camilo noriega, henry arguello. (2017). STOCHASTIC TRUNCATED WIRTINGER FLOW ALGORITHM FOR PHASE RETRIEVAL USING BOOLEAN CODED APERTURES. IEEE SigPort. http://sigport.org/1718
samuel pinilla, camilo noriega, henry arguello, 2017. STOCHASTIC TRUNCATED WIRTINGER FLOW ALGORITHM FOR PHASE RETRIEVAL USING BOOLEAN CODED APERTURES. Available at: http://sigport.org/1718.
samuel pinilla, camilo noriega, henry arguello. (2017). "STOCHASTIC TRUNCATED WIRTINGER FLOW ALGORITHM FOR PHASE RETRIEVAL USING BOOLEAN CODED APERTURES." Web.
1. samuel pinilla, camilo noriega, henry arguello. STOCHASTIC TRUNCATED WIRTINGER FLOW ALGORITHM FOR PHASE RETRIEVAL USING BOOLEAN CODED APERTURES [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1718

STOCHASTIC TRUNCATED WIRTINGER FLOW ALGORITHM FOR PHASE RETRIEVAL USING BOOLEAN CODED APERTURES

samuel pinilla

Paper Details

Authors:
samuel pinilla
samuel pinilla, camilo noriega, henry arguello
Submitted On:
11 March 2017 - 8:45pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

main.pdf

(712)

Keywords

Subscribe

Send Author a Private Message
[1] samuel pinilla, camilo noriega, henry arguello, "STOCHASTIC TRUNCATED WIRTINGER FLOW ALGORITHM FOR PHASE RETRIEVAL USING BOOLEAN CODED APERTURES", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1717. Accessed: May. 21, 2019.
@article{1717-17,
url = {http://sigport.org/1717},
author = {samuel pinilla; camilo noriega; henry arguello },
publisher = {IEEE SigPort},
title = {STOCHASTIC TRUNCATED WIRTINGER FLOW ALGORITHM FOR PHASE RETRIEVAL USING BOOLEAN CODED APERTURES},
year = {2017} }
TY - EJOUR
T1 - STOCHASTIC TRUNCATED WIRTINGER FLOW ALGORITHM FOR PHASE RETRIEVAL USING BOOLEAN CODED APERTURES
AU - samuel pinilla; camilo noriega; henry arguello
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1717
ER -
samuel pinilla, camilo noriega, henry arguello. (2017). STOCHASTIC TRUNCATED WIRTINGER FLOW ALGORITHM FOR PHASE RETRIEVAL USING BOOLEAN CODED APERTURES. IEEE SigPort. http://sigport.org/1717
samuel pinilla, camilo noriega, henry arguello, 2017. STOCHASTIC TRUNCATED WIRTINGER FLOW ALGORITHM FOR PHASE RETRIEVAL USING BOOLEAN CODED APERTURES. Available at: http://sigport.org/1717.
samuel pinilla, camilo noriega, henry arguello. (2017). "STOCHASTIC TRUNCATED WIRTINGER FLOW ALGORITHM FOR PHASE RETRIEVAL USING BOOLEAN CODED APERTURES." Web.
1. samuel pinilla, camilo noriega, henry arguello. STOCHASTIC TRUNCATED WIRTINGER FLOW ALGORITHM FOR PHASE RETRIEVAL USING BOOLEAN CODED APERTURES [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1717

A CONSTRAINED ADAPTIVE SCAN ORDER APPROACH TO TRANSFORM COEFFICIENT ENTROPY CODING

Ching-Han Chiang

Paper Details

Authors:
Ching-Han Chiang
Ching-Han Chiang, Jingning Han, Yaowu Xu
Submitted On:
8 March 2017 - 3:15am
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

ICASSP 2017 ADAPTIVE SCAN ORDER (4).pdf

(25)

Keywords

Subscribe

Send Author a Private Message
[1] Ching-Han Chiang, Jingning Han, Yaowu Xu, "A CONSTRAINED ADAPTIVE SCAN ORDER APPROACH TO TRANSFORM COEFFICIENT ENTROPY CODING", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1700. Accessed: May. 21, 2019.
@article{1700-17,
url = {http://sigport.org/1700},
author = {Ching-Han Chiang; Jingning Han; Yaowu Xu },
publisher = {IEEE SigPort},
title = {A CONSTRAINED ADAPTIVE SCAN ORDER APPROACH TO TRANSFORM COEFFICIENT ENTROPY CODING},
year = {2017} }
TY - EJOUR
T1 - A CONSTRAINED ADAPTIVE SCAN ORDER APPROACH TO TRANSFORM COEFFICIENT ENTROPY CODING
AU - Ching-Han Chiang; Jingning Han; Yaowu Xu
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1700
ER -
Ching-Han Chiang, Jingning Han, Yaowu Xu. (2017). A CONSTRAINED ADAPTIVE SCAN ORDER APPROACH TO TRANSFORM COEFFICIENT ENTROPY CODING. IEEE SigPort. http://sigport.org/1700
Ching-Han Chiang, Jingning Han, Yaowu Xu, 2017. A CONSTRAINED ADAPTIVE SCAN ORDER APPROACH TO TRANSFORM COEFFICIENT ENTROPY CODING. Available at: http://sigport.org/1700.
Ching-Han Chiang, Jingning Han, Yaowu Xu. (2017). "A CONSTRAINED ADAPTIVE SCAN ORDER APPROACH TO TRANSFORM COEFFICIENT ENTROPY CODING." Web.
1. Ching-Han Chiang, Jingning Han, Yaowu Xu. A CONSTRAINED ADAPTIVE SCAN ORDER APPROACH TO TRANSFORM COEFFICIENT ENTROPY CODING [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1700

Pre-processing And Classification Of Hyperspectral Imagery Via Selective Inpainting Presentation

Victoria Chayes

We propose a semi-supervised algorithm for processing and classification of hyperspectral imagery. For initialization, we keep 20% of the data intact, and use Principal Component Analysis to discard voxels from noisier bands and pixels. Then, we use either an Accelerated Proximal Gradient algorithm (APGL), or a modified APGL algorithm with a penalty term for distance between inpainted pixels and endmembers (APGL Hyp), on the initialized datacube to inpaint the missing data. APGL and APGL Hyp are distinguished by performance on datasets with full pixels removed or extreme noise.

Paper Details

Authors:
Victoria Chayes
Victoria Chayes, Kevin Miller, Rasika Bhalerao, Jiajie Luo, Wei Zhu, Andrea L. Bertozzi, Wenzhi Liao, Stanley Osher
Submitted On:
6 March 2017 - 2:08pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

ICASSP Presentation.pdf

(51)

Keywords

Subscribe

Send Author a Private Message
[1] Victoria Chayes, Kevin Miller, Rasika Bhalerao, Jiajie Luo, Wei Zhu, Andrea L. Bertozzi, Wenzhi Liao, Stanley Osher, "Pre-processing And Classification Of Hyperspectral Imagery Via Selective Inpainting Presentation", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1659. Accessed: May. 21, 2019.
@article{1659-17,
url = {http://sigport.org/1659},
author = {Victoria Chayes; Kevin Miller; Rasika Bhalerao; Jiajie Luo; Wei Zhu; Andrea L. Bertozzi; Wenzhi Liao; Stanley Osher },
publisher = {IEEE SigPort},
title = {Pre-processing And Classification Of Hyperspectral Imagery Via Selective Inpainting Presentation},
year = {2017} }
TY - EJOUR
T1 - Pre-processing And Classification Of Hyperspectral Imagery Via Selective Inpainting Presentation
AU - Victoria Chayes; Kevin Miller; Rasika Bhalerao; Jiajie Luo; Wei Zhu; Andrea L. Bertozzi; Wenzhi Liao; Stanley Osher
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1659
ER -
Victoria Chayes, Kevin Miller, Rasika Bhalerao, Jiajie Luo, Wei Zhu, Andrea L. Bertozzi, Wenzhi Liao, Stanley Osher. (2017). Pre-processing And Classification Of Hyperspectral Imagery Via Selective Inpainting Presentation. IEEE SigPort. http://sigport.org/1659
Victoria Chayes, Kevin Miller, Rasika Bhalerao, Jiajie Luo, Wei Zhu, Andrea L. Bertozzi, Wenzhi Liao, Stanley Osher, 2017. Pre-processing And Classification Of Hyperspectral Imagery Via Selective Inpainting Presentation. Available at: http://sigport.org/1659.
Victoria Chayes, Kevin Miller, Rasika Bhalerao, Jiajie Luo, Wei Zhu, Andrea L. Bertozzi, Wenzhi Liao, Stanley Osher. (2017). "Pre-processing And Classification Of Hyperspectral Imagery Via Selective Inpainting Presentation." Web.
1. Victoria Chayes, Kevin Miller, Rasika Bhalerao, Jiajie Luo, Wei Zhu, Andrea L. Bertozzi, Wenzhi Liao, Stanley Osher. Pre-processing And Classification Of Hyperspectral Imagery Via Selective Inpainting Presentation [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1659

Pages