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Rotation-Invariant Gait Identification with Quaternion Convolutional Neural Networks [article]

Bowen Jing, Vinay Prabhu, Angela Gu, John Whaley
2020 arXiv   pre-print
However, traditional Convolutional neural networks (CNNs) used in these systems compensate poorly for such transformations.  ...  In this paper, we target this problem by introducing Quaternion CNN, a network architecture which is intrinsically layer-wise equivariant and globally invariant under 3D rotations of an array of input  ...  Code The implementation of quaternion CNN is provided at Funding BJ and AG are each supported by a UnifyID AI Fellowship.  ... 
arXiv:2008.07393v1 fatcat:zwrrrrpfobdcbhcdetudrpgrj4

Personal‐specific gait recognition based on latent orthogonal feature space

Quan Zhou, Jianhua Shan, Bin Fang, Shixin Zhang, Fuchun Sun, Wenlong Ding, Chengyin Wang, Qin Zhang
2021 Cognitive Computation and Systems  
Omar et al. proposed a gait recognition approach for person re-identification, which takes multitask convolutional neural network models and extracted gait energy images (GEIs) to estimate the angle and  ...  Recurrent neural networks, such as long short-term memory (LSTM), have been widely This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution  ...  Fang et al. proposed the gait neural network (GNN) method based on temporal convolutional neural network (TCN), which can effectively recognises and predicts the human lower limb movement behaviour, and  ... 
doi:10.1049/ccs2.12007 fatcat:5y5jlpravfcezhdxtm32g2lffa

Orientation-Invariant Spatio-Temporal Gait Analysis Using Foot-Worn Inertial Sensors

Vânia Guimarães, Inês Sousa, Miguel Velhote Correia
2021 Sensors  
We demonstrate the invariance of our approach by simulating rotations of the sensor on the foot.  ...  In addition to being unrealistic to assume that the sensor can be aligned perfectly with the body, the robustness of gait analysis with respect to differences in sensor orientation has not yet been investigated—potentially  ...  [24] achieved relative errors of 0.0 ± 5.4 cm, using a deep convolutional neural network.  ... 
doi:10.3390/s21113940 fatcat:xorkquwlbramhl7uy4cmxvl4be

2020 Index IEEE Transactions on Image Processing Vol. 29

2020 IEEE Transactions on Image Processing  
Monsalve, J., +, TIP 2020 4003-4012 Steerable ePCA: Rotationally Invariant Exponential Family PCA.  ...  Ge, S., Ensemble of Deep Convolutional Neural Networks With Gabor Face Representations for Face Recognition.  ... 
doi:10.1109/tip.2020.3046056 fatcat:24m6k2elprf2nfmucbjzhvzk3m

Table of contents

2020 IEEE Transactions on Image Processing  
Chul Ye 1856 Attention-Aware Multi-Task Convolutional Neural Networks ................................ K. Lyu, Y. Li, and Z.  ...  Zhu 3254 Ensemble of Deep Convolutional Neural Networks With Gabor Face Representations for Face Recognition .......... .................................................................................  ... 
doi:10.1109/tip.2019.2940372 fatcat:h23ul2rqazbstcho46uv3lunku

2019 Index IEEE Transactions on Geoscience and Remote Sensing Vol. 57

2019 IEEE Transactions on Geoscience and Remote Sensing  
., Insect Biological Parameter Estimation Based on the Invariant Target Parameters of the Scattering Matrix; TGRS Aug. 2019 6212-6225 Hu, C., see Zhang, M., TGRS Sept. 2019 6666-6674 Hu, C., Zhang,  ...  Radar-Based Human Gait Recognition Using Dual-Channel Deep Convolutional Neural Network.  ...  ., +, TGRS July 2019 5028-5042 Radar-Based Human Gait Recognition Using Dual-Channel Deep Convolutional Neural Network.  ... 
doi:10.1109/tgrs.2020.2967201 fatcat:kpfxoidv5bgcfo36zfsnxe4aj4

Learning Neural Textual Representations for Citation Recommendation

Binh Thanh Kieu, Inigo Jauregi Unanue, Son Bao Pham, Hieu Xuan Phan, Massimo Piccardi
2021 2020 25th International Conference on Pattern Recognition (ICPR)  
Order Pattern for Grayscale-Inversion and Rotation Invariant Texture Classification DAY 3 -Jan 14, 2021 Jung, Cheolkon 1887 Deep Fusion of RGB and NIR Paired Images Using Convolutional Neural  ...  Chung, Hyunseung; Nam, Woo- Jeoung; Lee, Seong-Whan 1758 Rotation Invariant Aerial Image Retrieval with Group Convolutional Metric Learning DAY 2 -Jan 13, 2021 Tanaka, Tomohiro; Shinozaki,  ... 
doi:10.1109/icpr48806.2021.9412725 fatcat:3vge2tpd2zf7jcv5btcixnaikm

2021 Index IEEE Transactions on Image Processing Vol. 30

2021 IEEE Transactions on Image Processing  
Choi, H., +, TIP 2021 3321-3334 DRCNN: Dynamic Routing Convolutional Neural Network for Multi-View 3D Object Recognition.  ...  ., +, TIP 2021 5211-5222 SlimConv: Reducing Channel Redundancy in Convolutional Neural Networks by Features Recombining.  ... 
doi:10.1109/tip.2022.3142569 fatcat:z26yhwuecbgrnb2czhwjlf73qu

Machine Learning for Data-Driven Movement Generation: a Review of the State of the Art [article]

Omid Alemi, Philippe Pasquier
2019 arXiv   pre-print
To sample from Convolutional Neural Networks (CNNs), one has to reverse the flow of information in the network.  ...  Next, a feed-forward convolutional neural network is trained based on the representation learned by the convolutional autoencoder.  ... 
arXiv:1903.08356v1 fatcat:wtqawbramvdx3kz6ffgp2sv3ja

A review of computer vision-based approaches for physical rehabilitation and assessment

Bappaditya Debnath, Mary O'Brien, Motonori Yamaguchi, Ardhendu Behera
2021 Multimedia Systems  
However for many applications, like monitoring of functional rehabilitation of patients with musculo skeletal or physical impairments, the requirement is to comparatively evaluate human motion.  ...  [34] , the authors used a two-stream convolutional Siamese network for person re-identification.  ...  Deep Convolutional Neural Networks (DCNN) have been very successful in 2D human pose estimation [20, 50] and more recently, these networks are used for 3D pose estimation with much higher accuracy [  ... 
doi:10.1007/s00530-021-00815-4 fatcat:gpwx2pp6rba2vbtx7tvm2hozem

2021 Index IEEE Transactions on Instrumentation and Measurement Vol. 70

2021 IEEE Transactions on Instrumentation and Measurement  
Article numbers are based on specified topic areas and corresponding codes associated with the publication.  ...  ., +, TIM 2021 5002215 Semantic Segmentation With Light Field Imaging and Convolutional Neural Networks.  ...  ., +, TIM 2021 3509912 Convolutional Neural Network-Based Bayesian Gaussian Mixture for Intelligent Fault Diagnosis of Rotating Machinery.  ... 
doi:10.1109/tim.2022.3156705 fatcat:dmqderzenrcopoyipv3v4vh4ry

Latest Research Trends in Gait Analysis Using Wearable Sensors and Machine Learning: A Systematic Review

Abdul Saboor, Triin Kask, Alar Kuusik, Muhammad Mahtab Alam, Yannick Le Moullec, Imran Khan Niazi, Ahmed Zoha, Rizwan Ahmad
2020 IEEE Access  
It explores the recent papers along with the publication details and key parameters such as sampling rates, MLMs, wearable sensors, number of sensors, and their locations.  ...  Gait is the locomotion attained through the movement of limbs and gait analysis examines the patterns (normal/abnormal) depending on the gait cycle.  ...  Dense Clock Wise Recurrent Neural Network (DCWRNN) is proposed and compared with CWRNN [102] and Recurrent Neural Network (RNN) [103] in this study.  ... 
doi:10.1109/access.2020.3022818 fatcat:tfjtzbuilfgxhbi57dmshnccua

Online Tracking and Relocation Based on a New Rotation-Invariant Haar-like Statistical Descriptor in Endoscopic Examination

Haifan Gong, Limin Chen, Changhao Li, Jun Zeng, Xichen Tao, Yue Wang
2020 IEEE Access  
To effectively distinguish the target area from the gastrointestinal biopsy, we designed a new rotated invariant Haar-like statistical descriptor which is robust for rotating and illumination changes.  ...  INDEX TERMS Relocation, online tracking, Haar-like feature, random forest, Siamese network.  ...  SiamRPN applies off-line training convolution neural network to search the location of the tracking area in the next frame and obtain the location of the detection target boundary box and the confidence  ... 
doi:10.1109/access.2020.2994440 fatcat:pma4lcugefcvdke3xiai4gvufy

Survey on Style in 3D Human Body Motion: Taxonomy, Data, Recognition and its Applications

Sarah Ribet, Hazem Wannous, Jean-Philippe Vandeborre
2019 IEEE Transactions on Affective Computing  
definitions of style, describes the data that have been used up until now, introduces key notions about motion capture data as well as machine learning, and presents approaches about style recognition, person identification  ...  [15] used a deep forward neural network combined with a convolutional autoencoder.  ...  Note that all rotations were represented by quaternions.  ... 
doi:10.1109/taffc.2019.2906167 fatcat:qsq5wnke4zd6nkevp6knfmhmnq

Table of contents

2021 ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)  
, Zhi Chen, Liusheng Huang, University of Science and Technology of China, China IVMSP-31.2: ROTATION INVARIANCE ANALYSIS OF LOCAL CONVOLUTIONAL ....................................... 2170 FEATURES IN  ...  NEURAL NETWORKS DEAL WITH ALIASING ...................................... 2815 Antonio H.  ... 
doi:10.1109/icassp39728.2021.9414617 fatcat:m5ugnnuk7nacbd6jr6gv2lsfby
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