Scalable Multi-View Stereo Camera Array for Real-Time Image Capture and 3D Display in Real-World Applications

Ren Zhou

doi:10.54097/cyjs1142

Authors

Ren Zhou

DOI:

https://doi.org/10.54097/cyjs1142

Keywords:

Multi-view stereo camera array, Real-time image capture, AI-based object tracking, Image calibration, Geometric correction.

Abstract

3D display technology has advanced, finding applications in entertainment, healthcare, and education. However, existing multi-view content capture devices are limited by their reliance on single-camera setups or synthetic animations, constraining their flexibility and application range. This study proposes a scalable multi-view stereo camera array for real-time image capture and 3D display. The system uses 16 CMOS cameras, each with a resolution of 1920x1080 pixels, to synchronously capture multi-view images at 30 frames per second. Innovations include improved image calibration and geometric correction algorithms, completing each set of image calibration within 0.5 seconds with geometric correction accuracy of 0.1 pixels. The system also incorporates AI-based object tracking, capable of tracking targets moving at speeds up to 5 meters per second with 90% accuracy, and high-speed data transmission to ensure real-time image transfer with latency below 1 second. AI algorithms enhance performance in image calibration and object tracking. Machine learning techniques improve geometric correction accuracy and efficiency, while deep learning models ensure robust tracking in dynamic scenes. This system overcomes limitations of traditional single-camera setups and synthetic animations, offering improved capture efficiency and higher quality 3D images. It shows potential in multi-view facial recognition, stereo surgical training, and drone stereo monitoring. Future research will optimize image calibration and geometric correction algorithms, enhance object tracking stability, and explore additional application scenarios to improve system practicality and reliability.

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