Person Identification Based on Static Features Extracted from Kinect Skeleton Data

Zhao, Wenbing; Yang, Shunkun; Qiu, Tie; Luo, Xiong

doi:10.1109/smc52423.2021.9659013

Cited by 3 publications

(3 citation statements)

References 29 publications

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“…Refs. [ 98 , 101 , 102 ], often using Microsoft Kinect [ 37 , 97 , 100 , [103] , [104] , [105] , [106] , [107] , [108] , [109] , [110] , [111] , [112] , [113] , [114] , [115] , [116] , [117] ]for depth sensing or drawing from 3D models, Euclidean distances based on anthropometric survey data [ 118 , 119 ](e.g. CAESAR [ 23 ] [ 96 , [120] , [121] , [122] ])) or 2D as well as 3D pose estimation frameworks [ [123] , [124] , [125] , [126] , [127] , [128] , [129] , [130] , [131] , [132] , [133] , [134] ].…”

Section: Review Of Existing Researchmentioning

confidence: 99%

“…CAESAR [ 23 ] [ 96 , [120] , [121] , [122] ])) or 2D as well as 3D pose estimation frameworks [ [123] , [124] , [125] , [126] , [127] , [128] , [129] , [130] , [131] , [132] , [133] , [134] ]. Notably, only few publications propose anthropometric patterns as biometric features for identification on their own [ 98 , 105 , 116 , 131 ]. Instead they are usually combined with other descriptors like body shape [ 97 ] or gait [ 101 , 135 , 136 ].…”

Section: Review Of Existing Researchmentioning

confidence: 99%

See 1 more Smart Citation

Reconsideration of Bertillonage in the age of digitalisation: Digital anthropometric patterns as a promising method for establishing identity

Heuschkel,

Labudde

2024

Forensic Science International: Synergy

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Section: Review Of Existing Researchmentioning

confidence: 99%

Section: Review Of Existing Researchmentioning

confidence: 99%

Reconsideration of Bertillonage in the age of digitalisation: Digital anthropometric patterns as a promising method for establishing identity

Heuschkel,

Labudde

2024

Forensic Science International: Synergy

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“…Using a multi-layer perceptron, both feature vectors are then merged and explored together. Zhao et al [41] describe a technique that uses various classifiers to identify people. By using static characteristics taken from Kinect skeletal data, and used classfiers (KNN, decision tree, Gaussian Naive Bayesian, MultiLayer perceptron, and SVM) to predect the conclution.…”

Section: Related Workmentioning

confidence: 99%

Online hand position detection and classification system using multiple classification algorithms

Jaleel

Alabbasi

2022

IJEECS

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Hand position recognition is very significant for human-computer interaction. Different kinds of devices and technologies can be used for data acquisition; each has its specification and accuracy, one of these devices is Kinect V2 sensor. A three-dimensional location of the skeleton joints is taken from the Kinect device to create three types of data, the first is joint position raw data, the second is angles between joints, the third is combined of both types. These three types of data are used to train four classifiers, which are support vector machines, random forest, k nearest neighbors, and multilayer perceptron. The experiments are done on the datasets of 30,480 frames from 127 volunteers with saved trained models are used to predict and classify the eight positions of hand in a real-time system. The results show that our proposed approach performs well with highly efficient and accuracy reaching up to 99.07% in some cases and an average time spent on checking frame by frame sequentially very short period, and some cases, it reaches 0.59*10-3 seconds. This system can used in many applications such as controlling robots or devices, comparing physical exercises, or even monitoring elderly and patients, and more.

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Towards Frame-Level Person Identification Using Kinect Skeleton Data with Deep Learning

Zhao

2021

2021 IEEE Symposium Series on Computational Intelligence (SSCI)

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Person Identification Based on Static Features Extracted from Kinect Skeleton Data

Cited by 3 publications

References 29 publications

Reconsideration of Bertillonage in the age of digitalisation: Digital anthropometric patterns as a promising method for establishing identity

Reconsideration of Bertillonage in the age of digitalisation: Digital anthropometric patterns as a promising method for establishing identity

Online hand position detection and classification system using multiple classification algorithms

Towards Frame-Level Person Identification Using Kinect Skeleton Data with Deep Learning

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