ArticleComputational intelligence and neuroscience2022
Analysis of the Style Characteristics of National Dance Based on 3D Reconstruction.
Article in Computational intelligence and neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
National dance is an important symbol of national spiritual culture, as it embodies each nation's unique history, living habits, ideology, and culture. Many Chinese ethnic groups have developed their own dance forms and styles, each with their own set of charms. Strengthening our understanding of its style and characteristics is critical to our understanding of the national dance. To begin with, this paper proposes a patch-based multiview stereo reconstruction scheme that can accurately reconstruct 3D character models. The movement capture system then collects national dance movement data and uses them to drive a three-dimensional character model that generates dance visual animation. In the human skeleton model, a spatial-temporal HMM (hidden Markov model) is proposed that not only studies the temporal information of human movements but also the spatial information of adjacent connection points. The recognition rate of this algorithm increases to 95.68 percent when the number of setting points is increased to ten and to 98.28 percent when the number of setting points is increased to twenty, according to the research. The experimental results show that the 3D reconstruction model of ethnic dance developed in this paper is capable of meeting the goal of ethnic dance digitalization while being simple to use, being low in cost, and with a good display effect.
Indexed as
Identifiers
What OpenQuestion holds
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.