ArticleScientific reports2022
Design and implementation of virtual fitting system based on gesture recognition and clothing transfer algorithm.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
1 citing paper in PubMed, 10 citations in OpenAlex.
- Hierarchical graph contrastive learning of local and global presentation for multimodal sentiment analysis.Scientific reports · 2024Article
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
Abstract
Virtual fitting can bring fast and convenient fitting experience for people. The two core problems of virtual fitting system are human-computer interaction and clothing simulation. Interaction is an important factor in determining the fitting experience. The previous virtual fitting products usually use the mouse and keyboard interaction, and users rarely have a good sense of substitution and interaction. While, the method of using multiple cameras to take user images from different angles and then carry out posture recognition has the defect of low recognition accuracy. In view of clothing simulation and human-computer interaction of virtual fitting system, in order to achieve better customer immersion experience, this paper implemented a real-time interactive virtual fitting system based on Microsoft Kinect motion sensing device, and proposed a gesture determination algorithm based on finger recognition and an image transfer algorithm based on skeleton information matching. Using OpenNI development library and multi-threading technology, we have developed a motion-sensing capture module and a complete real-time virtual fitting system, and the system test results show that it has a good user experience.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.