☆ 4.6 Article

Multi-View Gait Recognition Based on a Siamese Vision Transformer

APPLIED SCIENCES-BASEL (2023)

相关参考文献

注意：仅列出部分参考文献，下载原文获取全部文献信息。

Article Computer Science, Artificial Intelligence

Multi-View Gait Recognition Based on Generative Adversarial Network

Jiamin Wen et al.

Summary: We proposed a new multi-view gait recognition model based on the generative adversarial network (GAN), which achieves the conversion and recognition of gait images through the introduction of a residual structure and view transformation. Experimental results show that the model has better recognition performance under different viewing angles and clothing.

NEURAL PROCESSING LETTERS (2022)

添加到收藏夹

Article Computer Science, Information Systems

Multiview Gait Recognition Based on Slack Allocation Generation Adversarial Network

Jing Gao et al.

Summary: By studying biological characteristics, it is found that gait information is unique to each person and can be used to identify identity information. However, gait information is often affected by factors such as viewing angle, dress, and carrying objects. To solve this problem, the idea of perspective transformation is proposed, using a generative adversarial network for transformation.

WIRELESS COMMUNICATIONS & MOBILE COMPUTING (2022)

添加到收藏夹

Article Engineering, Multidisciplinary

Human gait recognition subject to different covariate factors in a multi-view environment

Muhammad Asif et al.

Summary: This study aims to improve the accuracy of gait recognition technology by identifying different walking patterns of individuals under different covariates through analyzing publicly available images from the CASIA-B dataset. The experimental results show that clothing is the most easily recognizable covariate, while normal walking has a higher recognition accuracy.

RESULTS IN ENGINEERING (2022)

添加到收藏夹

Proceedings Paper Computer Science, Artificial Intelligence

Lagrange Motion Analysis and View Embeddings for Improved Gait Recognition

Tianrui Chai et al.

Summary: This paper analyzes the role of shape and motion cues in gait recognition and concludes that second-order information in the temporal dimension is necessary for identification, through the analysis of Lagrange’s equation. The authors design a second-order motion extraction module and a view-embedding module and demonstrate the effectiveness and interpretability of their method through experiments.

2022 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2022) (2022)

添加到收藏夹

Article Chemistry, Multidisciplinary

A Hard Example Mining Approach for Concealed Multi-Object Detection of Active Terahertz Image

Ling Li et al.

Summary: This paper provides a public dataset for evaluating multi-object detection algorithms in active terahertz imaging, which is more challenging compared to commonly used computer vision datasets. An image-based Hard Example Mining (HEM) scheme based on RetinaNet is designed, and several state-of-the-art detectors are evaluated on this dataset. Experimental results show that RetinaNet achieves the best mAP, and HEM further enhances the model performance.

APPLIED SCIENCES-BASEL (2021)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Multi-View Gait Image Generation for Cross-View Gait Recognition

Xin Chen et al.

Summary: Gait recognition aims to identify individuals based on their walking styles, offering advantages of non-contact and long-distance compared to other recognition methods. The development of deep learning has improved performance levels in cross-view gait recognition. The use of Multi-view Gait Generative Adversarial Network (MvGGAN) to generate fake gait samples has extended existing datasets and enhanced the performance of cross-view gait recognition methods.

IEEE TRANSACTIONS ON IMAGE PROCESSING (2021)

添加到收藏夹

Article Computer Science, Artificial Intelligence

A model-based gait recognition method with body pose and human prior knowledge

Rijun Liao et al.

PATTERN RECOGNITION (2020)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Grayscale-Thermal Tracking via Inverse Sparse Representation-Based Collaborative Encoding

Bin Kang et al.

IEEE TRANSACTIONS ON IMAGE PROCESSING (2020)

添加到收藏夹

Article Computer Science, Theory & Methods

A Survey on Gait Recognition

Changsheng Wan et al.

ACM COMPUTING SURVEYS (2019)

添加到收藏夹

Article Computer Science, Artificial Intelligence

GaitGANv2: Invariant gait feature extraction using generative adversarial networks

Shiqi Yu et al.

PATTERN RECOGNITION (2019)

添加到收藏夹

Article Computer Science, Information Systems

Vision-Based Gait Recognition: A Survey

Jasvinder Pal Singh et al.

IEEE ACCESS (2018)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Invariant feature extraction for gait recognition using only one uniform model

Shiqi Yu et al.

NEUROCOMPUTING (2017)

添加到收藏夹

Proceedings Paper Computer Science, Artificial Intelligence

GaitGAN: Invariant Gait Feature Extraction Using Generative Adversarial Networks

Shiqi Yu et al.

2017 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS (CVPRW) (2017)

添加到收藏夹

Proceedings Paper Computer Science, Artificial Intelligence

Lifting from the Deep: Convolutional 3D Pose Estimation from a Single Image

Denis Tome et al.

30TH IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2017) (2017)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Robust pedestrian detection in thermal infrared imagery using a shape distribution histogram feature and modified sparse representation classification

Xinyue Zhao et al.

PATTERN RECOGNITION (2015)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Recognizing Gaits Across Views Through Correlated Motion Co-Clustering

Worapan Kusakunniran et al.

IEEE TRANSACTIONS ON IMAGE PROCESSING (2014)

添加到收藏夹

Article Computer Science, Theory & Methods

View-Invariant Discriminative Projection for Multi-View Gait-Based Human Identification

Maodi Hu et al.

IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY (2013)

添加到收藏夹

Article Computer Science, Artificial Intelligence

View-independent human motion classification using image-based reconstruction

R. Bodor et al.

IMAGE AND VISION COMPUTING (2009)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Individual recognition using Gait Energy Image

J Han et al.

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2006)

添加到收藏夹

© Peeref 2019-2024. All rights reserved.