Dai, X., Zhao, R., Hu, P., & Munteanu, A. (2023). Measure4dhand: Dynamic Hand Measurement Extraction from 4D Scans. In 2023 IEEE International Conference on Image Processing (ICIP) (pp. 3543-3547). (Proceedings - International Conference on Image Processing, ICIP). IEEE. https://doi.org/10.1109/ICIP49359.2023.10222114

@inproceedings{502b69fcfac94fb5a81805d38f43ceac,
title = "Measure4dhand: Dynamic Hand Measurement Extraction from 4D Scans",
abstract = "Hand measurement is vital for hand-centric applications suchas glove design, immobilization design, protective gear design, to name a few. Vision-based methods have been previously proposed but are limited in their ability to only extract hand dimensions in a static and standardized posture(open-palm hand). However, dynamic hand measurementsshould be considered when designing these wearable products since the interaction between hands and products cannot be ignored. Unfortunately, none of the existing methodsare designed for measuring dynamic hands. To address thisproblem, we propose a user-friendly and fast method dubbedMeasure4DHand, which automatically extracts dynamic handmeasurements from a sequence of depth images captured bya single depth camera. Firstly, the ten dimensions of the handare defined. Secondly, a deep neural network is developedto predict landmark sequences for the ten dimensions frompartial point cloud sequences. Finally, a method is designedto calculate dimension values from landmark sequences. Anovel synthetic dataset consisting of 234K hands in variousshapes and poses, along with their corresponding ground truthlandmarks, is proposed for training the proposed methods.The experiment based on real-world data captured by a Kinectillustrates the evolution of the ten dimensions during handmovement, while the mean ranges of variation are also reported, providing valuable information for the hand wearableproduct design",
author = "Xinxin Dai and Ran Zhao and Pengpeng Hu and Adrian Munteanu",
note = "Funding Information: This work was supported in part by Innoviris under project AI43D and in part by Fonds Wetenschappelijk Onderzoek (FWO) under Project G094122N. Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE International Conference on Image Processing, ICIP ; Conference date: 08-10-2023 Through 11-10-2023",
year = "2023",
month = oct,
day = "8",
doi = "10.1109/ICIP49359.2023.10222114",
language = "English",
series = "Proceedings - International Conference on Image Processing, ICIP",
publisher = "IEEE",
pages = "3543--3547",
booktitle = "2023 IEEE International Conference on Image Processing (ICIP)",
url = "https://2023.ieeeicip.org/",
}