Abstract
This work, built on the Unity3D development platform, presents a way for merging feature extraction technology and Web3D technology into advertising design to effectively address the issues of poor efficiency and distortion in the field. Using the candidate text layout generating technique of visual salience, we first build the vector function set based on the three main colors, then we produce the visual communication partition model of advertising design. Next, the number of feature parameters of the shape advertising design is obtained via the establishment of coding coefficient constraint features and the use of an upgraded neural network technique to extract local feature parameter information about the product. Finally, the product design model is brought to life using Web3D technology to boost advertising design's productivity and accuracy. The experiments show that this method not only results in a high rate of correct product identification but also offers a fresh viewpoint on the visual communication of product advertising design by merging the two disciplines.
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