Year: 2025
Type: article
Abstract: Image-based viewpoint estimation is one of the tasks in image analysis, and another is the inverse problem of selecting the best viewpoint for displaying a three-dimensional object. Currently, two issues need further exploration in image-based viewpoint estimation research: insufficient labeled data and a limited number of evaluation methods for estimation results. To address the first issue, this paper proposes a spherical viewpoint sampling method based on a combination of analytical methods and motion adjustment, and designs a viewpoint-based projection image acquisition algorithm. Considering the difference between viewpoint inference and image classification, we propose an accuracy evaluation method with deviation angle tolerance for viewpoint estimation. Based on constructing a new dataset with viewpoint labels, the new accuracy evaluation method has been validated through experiments. The experimental results show that its estimation accuracy can reach 89% according to the new estimation evaluation indicators. Additionally, we applied our method to estimate the viewpoints of images from a furniture website and analyzed the viewpoint preferences in its furniture displays.
Source: Algorithms
DOI: 10.3390/a18040224
Authors: Meng Yuan, Hongjun Li
Institution: Beijing Forestry University
Language: English
Topic: Advanced Vision and Imaging
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,930
OpenAlex ID: W4409408724