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Method Tracks Fast-Moving Objects, Supports Autonomous Applications

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A team of researchers from Tsinghua University have developed a new 3D method that can be used to track fast-moving objects at high speeds. The real-time tracking approach, which is based on single-pixel imaging, could be used to improve autonomous driving, industrial inspection, and security surveillance systems.

“Our approach does not require reconstructing the object's image to calculate its position, which significantly reduces data storage and computational costs,” said research team leader Zihan Geng. “Specifically, acquiring a 3D coordinate requires only six bytes of storage space and 2.4 µs of computation time. By reducing computational costs and improving efficiency, it could lower the cost of equipment needed for high-speed tracking, making the technology more accessible and enabling new applications.”

The researchers demonstrated a tracking speed more than 200 times faster than traditional video-based methods. The tracking method does not require any prior motion information and can be performed with minimal computational resources.

The optics setup the researchers used to test their experiments. The experiments achieved a tracking rate of 6667Hz with a digital micromirror device at a modulation rate of 20kHz. Courtesy of Zihan Geng, Tsinghua University.
The optics setup the researchers used to test their experiments is shown. The experiments achieved a tracking rate of 6667 Hz with a digital micromirror device (DMD) at a modulation rate of 20 kHz. Courtesy of Zihan Geng, Tsinghua University.
Single-pixel imaging is a computational method that acquires measurements using a single detector, rather than the traditional array of pixels. It typically involves illuminating a scene with a sequence of patterns and then measuring the corresponding intensity values with a single-pixel detector.

To create a more practical single-pixel imaging system for object tracking, the researchers implemented a non-orthogonal projection approach, which is more efficient than the orthogonal method typically used. This involves projecting geometric light patterns onto two non-orthogonal planes, which creates 3D coordinates used to calculate the object's position. Non-orthogonal projection also reduces the overall system size, making it easier to assemble and implement.

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After validating their method using simulations, the researchers conducted experiments using a single-pixel imaging setup that included a 532 nm laser for active illumination, a digital micromirror device (DMD) with a 20 kHz modulation rate to create the light patterns, and two single-pixel detectors to collect the light signals.

To test the tracking ability, they allowed a metal sphere with a central hole to move down a curved spiral wire under gravity while being illuminated with light patterns. They used the detectors’ signals to calculate the object's 3D position and then used coordinate system rotation to obtain the calculated motion trajectory of the object. With this approach, they achieved a tracking rate of 6667 Hz with the DMD at a modulation rate of 20 kHz.

The researchers said that the primary challenge with this technology is that it can currently only be used to track a single object. But, as they are now developing methods that will allow multiple objects to be tracked with single-pixel imaging, they do have expectations of what this technology could be used for.

“This technology could enhance the perception abilities of technologies like self-driving cars, improve security surveillance systems, and offer more efficient monitoring and quality control for industrial inspection,” said Geng. “Additionally, this high-speed localization technique can be used in scientific research, such as insect flight trajectory studies.”

The research was published in Optics Letters (www.doi.org/10.1364/OL.521176).


Published: July 2024
Research & Technology3D tracking3D imagingsingle-pixel imagingindustrialsecuritydefenseautomationImagingOpticscamerasautomotiveLasersprojectionAmericasopticaTsinghua UniversityTechnology News

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