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This Radically Faster And Cheaper 3D Machine Vision Tech Uses Just A Single Pixel

Radically Faster, Cheaper 3D Machine Vision Uses Just A Single Pixel

Autonomous vehicles primarily depend on advanced sensors and significant computing power. However, Tsinghua University researchers in China have created a unique tracking system that lowers these requirements—only one pixel to detect an object accurately.

The Tsinghua University team has achieved a breakthrough with its 3D tracking technique. This technique significantly reduces the amount of computer power required while monitoring fast-moving objects at previously unknown speeds. The unique feature of their method is that it uses a single pixel rather than a full image.

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

Using little processing resources and no prior experience, the system can track things 200 times faster with this single-pixel methodology than with conventional video-based methods. The device measures the intensity of each pixel by projecting geometric light patterns onto the object in question. After that, it determines the object’s position and trajectory using advanced mathematics.

The researchers first used simulations. They then advanced to illuminating a metal sphere traveling along a curved spiral wire with a laser and a digital micro-mirror device (DMD). The system just needed the information from one pixel to do the required calculations.

The method can currently track a single object, however expanding this capability to track numerous objects is the next stage.

“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. “This high-speed localization technique can also be used in scientific research, such as insect flight trajectory studies.”

The team’s research findings were published in Optics Letters.

Source: Optica

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