Jumping spiders inspire ultra-efficient 3D camera

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Jumping spiders inspire ultra-efficient 3D camera

SpiderCam produces real-time 3D maps using less than a watt of power

EMBARGOED UNTIL 2:30 P.M. MDT (U.S.) ON SUNDAY, JUNE 7, 2026

• With poppy seed-sized brains, jumping spiders compute distances in a highly efficient manner
• Their eyes contain multiple retinal layers, each focused at a different depth
• By comparing differences in sharpness, they estimate distance
• New camera mimics this strategy while consuming less energy than a nightlight
• Camera could enable ultra-low-energy wearables, robots and drones

EVANSTON, Ill. - By borrowing a trick from tiny jumping spiders, Northwestern University engineers have developed an extremely energy-efficient 3D camera.

Called SpiderCam, the new device senses depth the same way that jumping spiders judge distances before making a high precision hop. To estimate depth, the system captures two images of the same scene with slightly different focus settings and measures subtle differences in blurriness between the two images. With this strategy, the camera produces real-time 3D maps while consuming less than a watt of power. That's less energy than used by a standard nightlight.

The innovation could enable a new generation of battery-powered devices that need to gauge their surroundings, like wearable technologies, assistive devices, robots and drones.

The study's co-first authors Marcos Ferreira and Tianao Li will present this work at 2:30 p.m. MDT on Sunday, June 7 at the Computer Vision Foundation's Conference on Computer Vision and Pattern Recognition (CVPR) in Denver. Complimentary registration is available for members of the media.

"Jumping spiders jump to catch prey, to avoid predators and to get around, and that requires excellent vision," said Northwestern's Emma Alexander, the study's corresponding author. "But their brains are very small - the size of a poppy seed - so they have to compute these distances in a highly efficient way. We wanted to understand whether we could borrow some of the same principles to create an extremely energy efficient depth sensor that could be used in resource-constrained situations where users don't have unlimited access to power."

An expert in bio-inspired computer vision, Alexander is an assistant professor of computer science at Northwestern's McCormick School of Engineering.

Most 3D cameras estimate depth either by comparing images from multiple viewpoints or by projecting and measuring light. While these approaches work well, they can require substantial computational power, expensive hardware and additional energy. To avoid power-hungry image matching and energy costs of projecting light, Alexander and her team looked to jumping spiders for inspiration.

Unlike human eyes, which each have one retina, jumping spiders have multiple layers of retinas in each eye. Each retinal layer captures an image focused at a slightly different distance. One layer might see an object sharply, while another sees the same object but slightly blurred.

"They see multiple levels of focus at all times," Alexander said. "So, they are always collecting pairs of images. Then, their brains could compare these differences in sharpness to judge distance."

SpiderCam uses a similar optical design. First, a custom camera simultaneously captures two images with slightly different focus settings. Acting as a translator between blur and distance, a custom algorithm then analyzes how the sharpness of edges and textures change between images. Finally, it converts those differences into depth measurements in real time.

Rather than running complex software on a conventional processor, the team built the algorithm directly into a low-power FPGA (field-programmable gate array), a customizable computer chip optimized for energy-efficient processing. The resulting prototype generates depth maps at 32.5 frames per second while consuming just 624 milliwatts of power. According to the researchers, SpiderCam is the first passive FPGA-based 3D camera system to operate below one watt.

Looking ahead, the researchers plan to improve the camera's optics, expand its field of view and integrate the technology into wearable devices and small robots. They also envision designing a custom chip that could slash power consumption even further, bringing 3D vision to applications where conventional depth sensors are impractical.

"I'm very interested in settings where you're very resource constrained and can't just plug a camera into a wall," Alexander said. "For example, it could be deployed in field settings with limited power. Separately, I also think it's particularly exciting for applications like augmented reality where you're interfacing with the physical world and need to know the locations of objects around you."

The study, "SpiderCam: Low-power snapshot depth from differential defocus," was partially supported by the National Science Foundation (CNS-2430327 and CCF-2431505).

Study photos

Emma Alexander

Corresponding author

Assistant professor of computer science

• [email protected]