SpiderCam: Low-Power Snapshot Depth from Differential Defocus

Fuente: arXiv
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Main Authors: Ferreira, Marcos A., Li, Tianao, Mamish, John, Hester, Josiah, Sangar, Yaman, Guo, Qi, Alexander, Emma
Format: Preprint
Published: 2026
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author Ferreira, Marcos A.
Li, Tianao
Mamish, John
Hester, Josiah
Sangar, Yaman
Guo, Qi
Alexander, Emma
author_facet Ferreira, Marcos A.
Li, Tianao
Mamish, John
Hester, Josiah
Sangar, Yaman
Guo, Qi
Alexander, Emma
contents We introduce SpiderCam, an FPGA-based snapshot depth-from-defocus camera which produces 480x400 sparse depth maps in real-time at 32.5 FPS over a working range of 52 cm while consuming 624 mW of power in total. SpiderCam comprises a custom camera that simultaneously captures two differently focused images of the same scene, processed with a SystemVerilog implementation of depth from differential defocus (DfDD) on a low-power FPGA. To achieve state-of-the-art power consumption, we present algorithmic improvements to DfDD that overcome challenges caused by low-power sensors, and design a memory-local implementation for streaming depth computation on a device that is too small to store even a single image pair. We report the first sub-Watt total power measurement for passive FPGA-based 3D cameras in the literature.
format Preprint
id arxiv_https___arxiv_org_abs_2603_17910
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle SpiderCam: Low-Power Snapshot Depth from Differential Defocus
Ferreira, Marcos A.
Li, Tianao
Mamish, John
Hester, Josiah
Sangar, Yaman
Guo, Qi
Alexander, Emma
Computer Vision and Pattern Recognition
We introduce SpiderCam, an FPGA-based snapshot depth-from-defocus camera which produces 480x400 sparse depth maps in real-time at 32.5 FPS over a working range of 52 cm while consuming 624 mW of power in total. SpiderCam comprises a custom camera that simultaneously captures two differently focused images of the same scene, processed with a SystemVerilog implementation of depth from differential defocus (DfDD) on a low-power FPGA. To achieve state-of-the-art power consumption, we present algorithmic improvements to DfDD that overcome challenges caused by low-power sensors, and design a memory-local implementation for streaming depth computation on a device that is too small to store even a single image pair. We report the first sub-Watt total power measurement for passive FPGA-based 3D cameras in the literature.
title SpiderCam: Low-Power Snapshot Depth from Differential Defocus
topic Computer Vision and Pattern Recognition
url https://arxiv.org/abs/2603.17910