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3D Hand Gesture Representation and Recognition through Deep Joint Distance Measurements
2020
International Journal of Advanced Computer Science and Applications
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Hand gestures with finger relationships are among the toughest features to extract for machine recognition. ...
In this paper, this particular research challenge is addressed with 3D hand joint features extracted from distance measurements which are then colour mapped as spatio temporal features. ...
angular displacement maps (JADMs) [37] , joint velocity maps (JVM) [38] , joint quad maps (JQM) [39] and joint trajectory maps (JTM) [40] . ...
doi:10.14569/ijacsa.2020.0110496
fatcat:6omi4iq4gjcudf2sqeh5deihxy
Skeleton based View Invariant Human Action Recognition using Convolutional Neural Networks
2019
International journal of recent technology and engineering
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In the second stage, the transformed joint locations of the skeletal data will be converted to RGB images by a color coding technique and forms a transformed joint location maps (TJLMs) . ...
His works focus on mechine learing, biomechanics, artificial intelligence, human motion analysis and sign language machine translation. ...
Concatenating the 3-color planes into one, creates a RGB image of joint angular displacement as intensity values. ...
doi:10.35940/ijrte.b3547.078219
fatcat:xiyh5cn47zfn3nm776amdrjaye
A Data Augmentation Method for Skeleton-Based Action Recognition with Relative Features
2021
Applied Sciences
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Because the generated color images are small in size, a shallow CNN model is suitable to extract the deep features of the generated motion images. ...
However, using relative features to depict human actions, in addition to preventing overfitting when the CNN model is trained on a few samples, is still a challenge. ...
For example, except for some subtle actions such as sign language or hand poses, the motion information of hand joints is redundant. ...
doi:10.3390/app112311481
fatcat:4ss67c6eqzhnvdlwbov24a4wf4
Multimodal Fusion Based on LSTM and a Couple Conditional Hidden Markov Model for Chinese Sign Language Recognition
2019
IEEE Access
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A novel multimodal fusion approach is proposed for Chinese sign language (CSL) recognition. ...
Then, as a result, the proposed skeleton-hand fusion framework can be used for the vision-based sign language recognition (SLR) of non-specific people in non-specific environments. ...
sign has also been interpreted using joint angular displacement maps (JADMs), which encode the sign as a color texture image [7] . ...
doi:10.1109/access.2019.2925654
fatcat:aqwbtp4afbe6lcphyxudxk6yra
Action Recognition Using 3D Histograms of Texture and A Multi-Class Boosting Classifier
2017
IEEE Transactions on Image Processing
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This paper presents a low-cost descriptor called 3D histograms of texture (3DHoTs) to extract discriminant features from a sequence of depth maps. 3DHoTs are derived from projecting depth frames onto three ...
Human action recognition is an important yet challenging task. ...
recognition, consisting of 12 gestures defined by American Sign Language (ASL). ...
doi:10.1109/tip.2017.2718189
pmid:28644810
fatcat:vyy6fauupbgpldw5k2wptzanye
GesSure- A Robust Face-Authentication enabled Dynamic Gesture Recognition GUI Application
[article]
2022
arXiv
pre-print
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2022 pre-print arXiv:2207.11033v1 fatcat:l2sxuyq3czct3gnalr7jtmtuci
The face model uses MTCNN and FaceNet to verify the user, and our LSTM-CNN architecture for gesture recognition, achieving an accuracy of 95% with five classes of gestures. ...
We use meaningful and relevant gestures for task operation, resulting in a better user experience. ...
Also, they are less intuitive since they use static gesture techniques like the American sign language models. ...
arXiv:2207.11033v2
fatcat:wffjotgr7fbcvplbpsf3ykvfqm
GesSure: A Robust Face-Authentic Enabled Dynamic Gesture Recognition GUI Application
2022
International Journal on Cybernetics & Informatics
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The face model uses MTCNN and FaceNet to verify the user, and our LSTM-CNN architecture for gesture recognition, achieving an accuracy of 95% with five classes of gestures. ...
We use meaningful and relevant gestures for task operation, resulting in a better user experience. ...
Also, they are less intuitive since they use static gesture techniques like the American sign language models. ...
doi:10.5121/ijci.2022.110402
fatcat:7yynxfbslrc7tpykjtosbukzia
Review on Vehicle Detection Technology for Unmanned Ground Vehicles
2021
Sensors
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Finally, promising research topics in the future study of vehicle detection technology for UGVs are discussed in detail. ...
Thirdly, several simulation platforms related to UGVs are presented for facilitating simulation testing of vehicle detection algorithms. ...
The overall framework of vehicle recognition technology for unmanned ground vehicles (UGVs).
Figure 3 . 3 Figure 3. Structure of vehicle detection algorithm overview in this survey. ...
doi:10.3390/s21041354
pmid:33672976
fatcat:ammlsccxbbhgpkx6r5vod7ciuy
A Comparative Review on Applications of Different Sensors for Sign Language Recognition
2022
Journal of Imaging
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A sensor-based smart glove for sign language recognition (SLR) proved helpful to generate data based on various hand movements related to specific signs. ...
A detailed comparative review of all types of available techniques and sensors used for sign language recognition was presented in this article. ...
Color texture coded-based joint angular displacement maps were classified efficiently with the help of a 3-D deep CNN model. ...
doi:10.3390/jimaging8040098
pmid:35448225
pmcid:PMC9027924
fatcat:ocodirl2frht7pf6jflorjs2we
A Review on Deep Learning Approaches for 3D Data Representations in Retrieval and Classifications
2020
IEEE Access
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Therefore, it can be concluded that deep learning together with a suitable 3D data representation gives an effective approach for improving the performance of 3D shape analysis. ...
For more information, see https://creativecommons.org/licenses/by/4.0/ VOLUME 8, 2020 ...
It gives a 2.5D data about the obtained 3D object by giving the depth map (D) together with color information (RGB). ...
doi:10.1109/access.2020.2982196
fatcat:jnya5rscynf3zm7efuucqxafri
Analysis of the Influence of Training Data on Road User Detection
2018
2018 IEEE International Conference on Vehicular Electronics and Safety (ICVES)
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Stiller and the other members of the MRT team for the four months that I spent there. ...
Also, thanks to the members of the scientific community who made this thesis possible by publicly releasing databases and source code. ...
Figure A. 3 : 3 Examples of lane detection and classification results using the proposed approach. Color code: pink for solid, blue for dashed and red for merging.
CNN. ...
doi:10.1109/icves.2018.8519510
dblp:conf/icves/Guindel0AS18
fatcat:fu3cvrvkdjeivndsipd4hnhnqy
Neural Radiance Fields: Past, Present, and Future
[article]
2024
arXiv
pre-print
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led to a boom in Computer Graphics, Robotics, Computer Vision, and the possible scope of High-Resolution Low Storage Augmented Reality and Virtual Reality-based 3D models have gained traction from res with ...
In doing so, this survey categorizes all the NeRF-related research in terms of the datasets used, objective functions, applications solved, and evaluation criteria for these applications. ...
This integration allows effective embedding of 3-D scene information into an observed image, overcoming the limitations of previous works that used joint aperture-exposure coding only for reconstructing ...
arXiv:2304.10050v2
fatcat:ixgkwqkt25gqdipgq4er6pdej4
Action in Mind: A Neural Network Approach to Action Recognition and Segmentation
[article]
2021
arXiv
pre-print
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For each level of development the system is trained with the input data consisting of consecutive 3D body postures and tested with generalized input data that the system has never met before. ...
This thesis presents a novel computational approach for human action recognition through different implementations of multi-layer architectures based on artificial neural networks. ...
There are indeed several applications for these systems including video surveillance, human-computer interaction, video retrieval, sign language recognition, robotics (social robotics), health care, video ...
arXiv:2104.14870v1
fatcat:cp7gnx34jbdq5o45zbfmhlrhlm
BIOSIG 2020 - Komplettband
2020
Biometrics and Electronic Signatures
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We address that by presenting a specifically collected database containing three session, each with three different capture instructions, to simulate realistic use cases. ...
Face recognition has become essential in our daily lives as a convenient and contactless method of accurate identity verification. ...
We thank the reviewers for their comments, the authors in [MSK06] for providing us with their codes for reconstructing faces, and NCI Australia for computational resources. ...
dblp:conf/biosig/X20
fatcat:hkqvegujqbatdlopbzclkxdive
BIOSIG 2021 - Complete Volume
2021
Biometrics and Electronic Signatures
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The problem of distinguishing identical twins and non-twin look-alikes in automated facial recognition (FR) applications has become increasingly important with the widespread adoption of facial biometrics ...
The proposed network provides a quantitative similarity score for any two given faces and has been applied to large-scale face datasets to identify similar face pairs. ...
TOC Biometrics, R+D Center SR-226, supported this work. ...
dblp:conf/biosig/X21
fatcat:susbfwcwi5dljbhxc4xxyv6dnq
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