Artificial Intelligence Recognition Simulation of 3D Multimedia Visual Image Based on Sparse Representation Algorithm

Chen, Weixiao

doi:10.1109/access.2020.3006774

Cited by 10 publications

(4 citation statements)

References 39 publications

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“…ImageNet is an image dataset organized according to the WordNet hierarchical structure. 600 images of different types are selected from the database [17]. ere are 6 datasets, and the parameters of each dataset are shown in Table 1.…”

Section: Experimental Data Settingsmentioning

confidence: 99%

Design and Reconstruction of Visual Art Based on Virtual Reality

Bai

2021

Security and Communication Networks

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Because traditional methods generally lack the image preprocessing link, the effect of visual image detail processing is not good. In order to enhance the image visual effect, a visual art design method based on virtual reality is proposed. Wavelet transform method is used to denoise the visual image and the noise signal in the image is removed; a binary model of fuzzy space vision fusion is established, the space of the visual image is planned, and the spatial distribution information of the visual image is obtained. According to the principle of light and shadow phenomenon in visual image rendering, the Extend Shadow map algorithm is used to render the visual image. Virtual reality technology was used to reconstruct the preprocessed visual image, and the ant colony algorithm was used to optimize the visual image to realize the visual image design. The results show that the peak signal-to-noise ratio of the visual image processed by the proposed method is high, and the image detail processing effect is better.

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Section: Experimental Data Settingsmentioning

confidence: 99%

Design and Reconstruction of Visual Art Based on Virtual Reality

Bai

2021

Security and Communication Networks

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“…Without artistic language, there is no work of art. The language of interactive art comes from his media on the one hand, on the other hand also from its interactive means and technology [5][6].…”

Section: The Language Of Interactive Artmentioning

confidence: 99%

Design of AI Interactive Art System Based on Computer Vision

2023

IJAID

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With the continuous development of artificial intelligence technology, under the support and promotion of big data and cloud computing, with its own sustainable work, extremely fast computing speed and a certain degree of intelligence more and more deep into people's life, in recent years also into the field of design. This paper aims to study the design of AI interactive art systems based on computer vision. This paper on the new media era of interactive art and the development of the database is briefly introduced, to explore the structural similarity of the database and interactive art, then further to the human interactive art is the most important and most important interactive object psychology and emotional analysis, for the database and human similarity theory analysis and the coexistence in human and database emotion and the combination of the creation of interactive art. A brief analysis of artificial intelligence and big data related to databases in a broad sense is conducted, to explore their application in interactive art, the emotional changes brought about by interactive art, and the possibilities and ethical problems of future interactive art based on these technologies and emotions. Artificial intelligence art will become the foundation of the art model in the 21st century. For interactive art creators, human-computer interaction, human interaction and even machine interaction will become a part of the future interactive art. How to truly grasp this technology and correctly transfer emotion is an opportunity for the future interactive art creators and a challenge.

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“…For example, several recognition tasks use distinct techniques for extracting features. Object identification often involves scale-invariant feature transformation [3], whereas face recognition depends on local binary pattern features [4]. Additionally, pedestrian detection utilizes histograms of oriented gradient features [5].…”

Section: Introductionmentioning

confidence: 99%