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SACA Net: Cybersickness Assessment of Individual Viewers for VR Content via Graph-Based Symptom Relation Embedding 1

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16th European Conference on Computer Vision, ECCV 2020

作者： Lee, Sangmin Kim, Jung Uk Kim, Hak Gu Kim, Seongyeop Ro, Yong Man Image and Video Systems Lab School of Electrical Engineering KAIST Daejeon Korea Republic of Signal Processing Lab Institute of Electrical Engineering EPFL Lausanne Switzerland

ISBN: (数字)9783030585921

ISBN: (纸本)9783030585914

Recently, cybersickness assessment for VR content is required to deal with viewing safety issues. Assessing physical symptoms of individual viewers is challenging but important to provide detailed and personalized guides for viewing safety. In this paper, we propose a novel symptom-aware cybersickness assessment network (SACA Net) that quantifies physical symptom levels for assessing cybersickness of individual viewers. The SACA Net is designed to utilize the relational characteristics of symptoms for complementary effects among relevant symptoms. The proposed network consists of three main parts: a stimulus symptom context guider, a physiological symptom guider, and a symptom relation embedder. The stimulus symptom context guider and the physiological symptom guider extract symptom features from VR content and human physiology, respectively. The symptom relation embedder refines the stimulus-response symptom features to effectively predict cybersickness by embedding relational characteristics with graph formulation. For validation, we utilize two public 360-degree video datasets that contain cybersickness scores and physiological signals. Experimental results show that the proposed method is effective in predicting human cybersickness with physical symptoms. Further, latent relations among symptoms are interpretable by analyzing relational weights in the proposed network. © 2020, Springer Nature Switzerland AG.

关键词： Embeddings

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AIM 2020 Challenge on image Extreme Inpainting 16th

AIM 2020 Challenge on Image Extreme Inpainting

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Workshops held at the 16th European Conference on Computer Vision, ECCV 2020

作者： Ntavelis, Evangelos Romero, Andrés Bigdeli, Siavash Timofte, Radu Hui, Zheng Wang, Xiumei Gao, Xinbo Shin, Chajin Kim, Taeoh Son, Hanbin Lee, Sangyoun Li, Chao Li, Fu He, Dongliang Wen, Shilei Ding, Errui Bai, Mengmeng Li, Shuchen Zeng, Yu Lin, Zhe Yang, Jimei Zhang, Jianming Shechtman, Eli Lu, Huchuan Zeng, Weijian Ni, Haopeng Cai, Yiyang Li, Chenghua Xu, Dejia Wu, Haoning Han, Yu Nadim, Uddin S. M. Jang, Hae Woong Ahmed, Soikat Hasan Yoon, Jungmin Jung, Yong Ju Li, Chu-Tak Liu, Zhi-Song Wang, Li-Wen Siu, Wan-Chi Lun, Daniel P. K. Suin, Maitreya Purohit, Kuldeep Rajagopalan, A.N. Narang, Pratik Mandal, Murari Chauhan, Pranjal Singh Computer Vision Lab ETH Zürich Zürich Switzerland CSEM Neuchâtel Switzerland School of Electronic Engineering Xidian University Xi’an China Image and Video Pattern Recognition Laboratory School of Electrical and Electronic Engineering Yonsei University Seoul Korea Republic of Baidu Inc. Beijing China Beijing China Dalian University of Technology Dalian China Adobe San Jose United States Rensselaer Polytechnic Institute Troy United States Peking University Beijing China Lab Gachon University Seongnam Korea Republic of Centre for Multimedia Signal Processing Department of Electronic and Information Engineering The Hong Kong Polytechnic University Hong Kong China Indian Institute of Technology Madras Chennai India BITS Pilani Pilani India MNIT Jaipur Jaipur India

ISBN: (纸本)9783030670696

This paper reviews the AIM 2020 challenge on extreme image inpainting. This report focuses on proposed solutions and results for two different tracks on extreme image inpainting: classical image inpainting and semantically guided image inpainting. The goal of track 1 is to inpaint large part of the image with no supervision. Similarly, the goal of track 2 is to inpaint the image by having access to the entire semantic segmentation map of the input. The challenge had 88 and 74 participants, respectively. 11 and 6 teams competed in the final phase of the challenge, respectively. This report gauges current solutions and set a benchmark for future extreme image inpainting methods. © 2020, Springer Nature Switzerland AG.

关键词： Semantic Segmentation

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Advancements in computer aided methods for EEG-based epileptic detection

Advancements in computer aided methods for EEG-based epilept...

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7th International Conference on Bio-Inspired Systems and signal processing, BIOsignalS 2014 - Part of 7th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2014

作者： Ahmad, Malik Anas Majeed, Waqas Khan, Nadeem Ahmad Signal Image and Video Processing Lab SBASSE LUMS Lahore Pakistan Robotics and Intelligent Systems Engineering Lab SMME NUST Islamabad Pakistan

ISBN: (纸本)9789897580116

During the diagnosis of epilepsy, computer aided methods can significantly supplement a neurologist by automatically identifying the epileptic patterns in an EEG. In the last decade immense amount of work has been done in the field of EEG based computer aided diagnosis of epilepsy. Even after so much work these tools are not getting used up to their full potential. In this paper we have very briefly discussed some of the previously used signal processing and machine learning techniques which are proposed for epileptic pattern detection. We have concluded this paper by suggesting some additions in the previous method which can make these systems more helpful, detailed and precise for the neurologist. Copyright © 2014 SCITEPRESS - Science and Technology Publications. All rights reserved.

关键词： Electroencephalography

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Computer Assisted Analysis System of Electroencephalogram for Diagnosing Epilepsy

Computer Assisted Analysis System of Electroencephalogram fo...

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International Conference on Pattern Recognition

作者： Malik Anas Ahmad Nadeem Ahmad Khan Waqas Majeed EE SBASSE LUMS Signal Image & Video Processing Lab Lahore Pakistan

ISBN: (纸本)9781479952106

Automation of Electroencephalogram (EEG) analysis can significantly help the neurologist during the diagnosis of epilepsy. During last few years lot of work has been done in the field of computer assisted analysis to detect an epileptic activity in an EEG. Still there is a significant amount of need to make these computer assisted EEG analysis systems more convenient and informative for a neurologist. After briefly discussing some of the existing work we have suggested an approach which can make these systems more helpful, detailed and precise for the neurologist. In our proposed approach we have handled each epoch of each channel for each type of epileptic pattern exclusive to each other. In our approach feature extraction starts with an application of multilevel Discrete Wavelet Transform (DWT) on each 1 sec non-overlapping epochs. Then we apply Principal Component Analysis (PCA) to reduce the effect of redundant and noisy data. Afterwards we apply Support Vector Machine (SVM) to classify these epochs as Epileptic or not. In our system a user can mark any mistakes he encounters. The concept behind the inclusion of the retraining is that, if there is more than one example with same attributes but different labels, the classifier is going to get trained to the one with most population. These corrective marking will be saved as examples. On retraining the classifier will improve its classification, hence it will tries to adapt the user. In the end we have discussed the results we have acquired till now. Due to limitation in the available data we are only able to report the classification performance for generalised absence seizure. The reported accuracy is resulted on very versatile dataset of 21 patients from Punjab Institute of Mental Health (PIMH) and 21 patients from Children Hospital Boston (CHB) which have different number of channel and sampling frequency. This usage of the data proves the robustness of our algorithm.

关键词： Electroencephalography Accuracy Discrete wavelet transforms Epilepsy Principal component analysis Feature extraction Support vector machines

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Automatic sign language recognition: Vision based feature extraction and probabilistic recognition scheme from multiple cues 08

Automatic sign language recognition: Vision based feature ex...

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1st International Conference on Pervasive Technologies Related to Assistive Environments, PETRA 2008

作者： Caridakis, George Diamanti, Olga Karpouzis, Kostas Maragos, Petros Image Video and Multimedia Systems Lab. National Technical University of Athens Iroon Polytexneiou 9 15780 Athens Greece Computer Vision Speech Communication and Signal Processing Group National Technical University of Athens Iroon Polytexneiou 9 15780 Athens Greece

ISBN: (纸本)9781605580678

This work focuses on two of the research problems comprising automatic sign language recognition, namely robust computer vision techniques for consistent hand detection and tracking, while preserving the hand shape contour which is useful for extraction of features related to the handshape and a novel classification scheme incorporating Self-organizing maps, Markov chains and Hidden Markov Models. Geodesic Active Contours enhanced with skin color and motion information are employed for the hand detection and the extraction of the hand silhouette, while features extracted describe hand trajectory, region and shape. Extracted features are used as input to separate classifiers, forming a robust and adaptive architecture whose main contribution is the optimal utilization of the neighboring characteristic of the SOM during the decoding stage of the Markov chain, representing the sign class. Copyright 2008 ACM.

关键词： image segmentation

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3CCD interpolation using selective projection

3CCD interpolation using selective projection

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2005 IEEE International Conference on Acoustics, Speech, and signal processing, ICASSP '05

作者： Bae, Soo Hyun Kim, Moon-Cheol Juang, Biing-Hwang Center for Signal and Image Processing Georgia Institute of Technology Atlanta GA United States Video Lab. Digital Media RandD Center Samsung Electronics Co. Ltd. Suwon Korea Republic of

ISBN: (纸本)0780388747

Emerging of HDTV accelerates evolution of high-resolution imaging system. A 3CCD digital camera system has been developed for higher resolution than a CCD imaging has. From the pixel correlation caused by half-pixel shift of the green channel, we can interpolate pixels and get four times higher resolution of color image. The proposed method involves three projection operators. The first is to reduce aliasing of image regions by selective projection in subband channels. The second projection makes inverse of MTF which generates blurring over the entire image. The last operator works for fast convergence. From the experimental result, the proposed algorithm shows suppression of jagging effects and restoration of aliased image regions. It is experimentally shown that the projection process converges and is almost finished at the first iteration. © 2005 IEEE.

关键词： Charge coupled devices

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Automated Characterization of cellular migration phenomena

Automated Characterization of cellular migration phenomena

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2005 IEEE Computational Systems Bioinformatics Conference, Workshops and Poster Abstracts

作者： Beaudry, Christian Berens, Michael E. Doker, Tarek El Joy, Anna M. Karam, Lina J. Lacroix, Zoe Lutfi, Jad A. Motoru, Sai Renaut, Rosemary A. Rich, Ian J. Translational Genomics Research Institute Phoenix AZ United States Department of Electrical Engineering Machine Perception Laboratory Northern Arizona University United States Department of Electrical Engineering Image Video and Usability and Multi-D Signal Processing Labs. Arizona State University United States Department of Mechanical and Aerospace Engineering Scientific Data Management Lab. Arizona State University United States Department of Mathematics Computational Biosciences Program Arizona State University United States

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An adaptive coding scheme using affine motion model for MPEG P-VOP

An adaptive coding scheme using affine motion model for MPEG...

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Proceedings - IEEE International Conference on Acoustics, Speech, and signal processing

作者： Li, Xiaohuan Jackson, Joel R. Katsaggelos, Aggelos K. Mersereau, Russell M. Ctr. for Image and Signal Processing Georgia Institute of Technology Atlanta GA United States Image and Video Processing Lab. Northwestern University Evanston IL United States

Block matching has been used for motion estimation and motion compensation in MPEG standards for years. While it has an acceptable performance in describing motion between frames, it requires quite a few bits to represent the motion vectors. In certain circumstances, the use of whole frame affine motion models would perform equally well or even better than block matching in terms of motion accuracy, while it results in the coding of only 6 parameters. In this paper, we modify an MPEG-4 codec by adding (1) 6 affine model parameters to the frame header, (2) mode selection among INTRA, SKIP, INTER-16×16, INTER-8×8, and GLOBAL-AFFINE modes by Lagrange optimal rate-distortion criteria. Simulation results demonstrate 10-20% decrease in bit-rate, compared to the MMS' codec for an average coded P-frame with the same reconstruction PSNR.

关键词： Motion estimation

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Interactive tools for signal processing education. The signal processing instructional facility (SPIF lab) at Washington State University

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Computer Applications in Engineering Education 1993年第6期1卷 517-517页

作者： Bamberger, R.H. Signal Processing Instructional Facility School of Electrical Engineering and Computer Science Washington State University Pullman WA 99164-2752 Dr. Roberto H. Bamberger:was born on January 30 1965 in Buenos Aires Argentina. He received his B.E.E and PhD from the Georgia Institute of Technology in 1986 and 1990 respectively. Currently Dr. Bamberger is an assistant professor in the School of Electrical Engineering and Computer Science at Washington State University. Dr. Bamberger's research program is focused on the design implementation and application of multidimensional multirate filter banks subband image and video compression analysis of nonstationary data and application of digital signal processing techniques in the design of analog and mixed-mode integrated circuits. Dr. Bamberger is the founder and director of the Signal Processing Instructional Facility (SPIF Lab) at Washington State University. The SPIF Lab features interactive multimedia-based tools for teaching concepts related to linear systems theory. Dr. Bamberger is active in developing multimedia-based instructional laboratories for a variety of other topics as well. In addition to his teaching and research programs Dr. Bamberger is an associate editor for theIEEE Transactions on Signal Processingand a member of the editorial board forComputer Applications in Engineering Education. Dr. Bamberger is also advisor to the WSU Student Branch of the IEEE and assistant director of the WSU Cougar Marching Band. Dr. Bamberger is a member of Phi Eta Sigma Eta Kappa Nu Tau Beta Pi and Kappa Kappa Psi.

The signal processing Instructional Facility (SPIF lab) is an experiment in using in interactive multimedia for teaching concepts related to linear systems theory and signal processing. The goals of the SPIF lab are to augment, enhance, and interconnect sophomore, junior, and senior level courses with the common thread of linear systems and transforms by unifying the experimentation medium. In this fashion, physical phenomenon is returned to the forefront of engineering education. The laboratory features powerful Mathematica Notebooks (a form of hypertext) and interactive applications that use dedicated DSP microprocessors.

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