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Depth and Dimension Estimation Using Computer Vision

Publication Type : Conference Paper

Publisher : IEEE

Source : 2025 International Conference on Wireless Communications Signal Processing and Networking (WiSPNET)

Url : https://doi.org/10.1109/wispnet64060.2025.11004896

Campus : Coimbatore

School : School of Computing

Year : 2025

Abstract : The growing importance of depth and dimension estimation in robotics, autonomous vehicles, and construction industries highlights the need for accurate environmental perception. Monocular depth-based cameras face challenges such as scale ambiguity and data scarcity, making precise distance measurements difficult. Stereo-vision setups provide improved scene information, thereby reducing the error rate. Deriving depth from stereo images using a Pseudo-LIDAR based approach enhances depth data. Pixel-to-length conversion from this depth information enables precise dimension estimation of objects. Developing a computer vision algorithm that calculates pixel-to-length ratios at various distances and adjusting for calibration discrepancies will streamline decision-making in autonomous systems, improving efficiency across industrial operations.

Cite this Research Publication : Ravindran S, Srikanth S, Raagul T S, Madhankumar R M, Ganesan M, Depth and Dimension Estimation Using Computer Vision, 2025 International Conference on Wireless Communications Signal Processing and Networking (WiSPNET), IEEE, 2025, https://doi.org/10.1109/wispnet64060.2025.11004896

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