SpiderCam: Low-Power Snapshot Depth from Differential Defocus

2026-03-18

AI Summary

This work proposes SpiderCam, an FPGA-based snapshot depth camera designed to address the computational and memory constraints of passive depth sensing on small, low-power devices. The system integrates a custom dual-focus optical design with a disparity-from-defocus depth (DfDD) algorithm optimized for low-power sensors, implemented in SystemVerilog on a low-power FPGA using a memory-localized streaming compute architecture. Operating at a working distance of up to 52 cm, SpiderCam delivers real-time sparse depth maps at 480×400 resolution and 32.5 frames per second, with a total system power consumption of only 624 mW. This represents the first passive FPGA-based 3D camera with sub-watt power consumption, achieving state-of-the-art energy efficiency among comparable systems.

Technology Category

• Computer Vision: Computational Photography, Image & Video Synthesis
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization
• Search and Optimization: Distributed Search

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Search and Retrieval-Augmented AI: Efficiency and scalability of Web search engines
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

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.

Problem

• low-power
• snapshot depth
• depth from defocus
• FPGA
• 3D camera

Innovation

• depth-from-defocus
• low-power FPGA
• snapshot depth sensing
• memory-local processing
• real-time 3D imaging