Evidence map›Paper›PMID 36172324›Full record

ArticleComputational intelligence and neuroscience2022

Intelligent Animation Creation Method Based on Spatial Separation Perception Algorithm.

Qingbo Meng

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Qingbo MengQingdao Agricultural University, College of Animation and Media, Qingdao 266109, Shandong, China.ORCID https://orcid.org/0000-0001-5694-4076

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the computer group animation creation technology, the artificial life method of computer animation overcomes the defects of traditional animation creation technology and greatly improves the animation creation efficiency. However, due to the increasing complexity of the animation character modeling technology used in this method, the coupling degree between the models of the animation system is also increasing, which makes the animation creation increasingly difficult. Especially, when the number of characters' increases, the computation will increase rapidly in a nonlinear way, which greatly affects the real-time animation creation and limits the wide application of this method. In this paper, we have conducted an in-depth study and implementation of the design of the animation character model and its implementation technology, analyzed and designed the group animation character model, and designed the space separation perception algorithm to effectively reduce the design difficulty of the character biomechanical model, reduce the amount of computation, and further ensure the real time of large-scale group animation creation. Therefore, the research reduces the coupling between animation system models without reducing the animation effect and real-time performance. It reduces the amount of computer operation, meets the real-time requirements of large-scale group animation creation, and has important significance and value.

Indexed as

AlgorithmsComputer GraphicsPerception

Identifiers

PMID36172324
PMCPMC9512613

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.