ToF tech news

Melexis Announces ToF Chipset and Evaluation Kit

Image Sensors World - 19. January 2017 - 18:34
Melexis announces a chipset and its evaluation kit for ToF 3D vision. Representing a complete ToF sensor and control solution, the chipset supports QVGA resolution and offers unsurpassed sunlight robustness and up to -40°C to +105°C temperature range operation, so that designers can test this automotive-qualified chipset.

The Melexis chipset includes MLX75023 1/3-inch optical format ToF sensor and the MLX75123, a companion IC that controls the sensor and illumination unit and delivers data to a host processor. The EVK75123 QVGA evaluation kit combines a sensor board featuring the chipset, an 12-LED illumination module, an interface board and a processor module:


The MLX75023 sensor has QVGA resolution and background light rejection capabilities of up to 120klux. This IC can provide raw data output in less than 1.5 ms, giving it capacity to track rapid movement.

Melexis also publishes a Youtube video with their ToF system demo:

PMD/Infineon ToF Sensor in Asus ZenFone AR

Image Sensors World - 8. January 2017 - 19:23
Infineon and PMD REAL3 ToF image sensor is at the heart of Asus ZenFone AR. The ASUS Zenfone AR is said to be the world’s thinnest smartphone that offers a 3D ToF camera and the first Google Daydream and Tango ready smartphone.

3D scanning with semiconductors from Infineon helps to interconnect the real and virtual worlds,” said Martin Gotschlich, Director, 3D Imaging at Infineon Technologies. “Mobile devices with an integrated 3D image sensor have spatial awareness of their surroundings and the capability for augmented reality applications with an impressive realistic quality. They pave the way for numerous applications and innovations that were not previously possible.

Scandy publishes a use case example for the new Asus smartphone:

ToF Camera Error Analysis and Correction

Image Sensors World - 7. January 2017 - 11:56
Sensors journal publishes an open-access paper "Depth Errors Analysis and Correction for Time-of-Flight (ToF) Cameras" by Ying He, Bin Liang, Yu Zou, Jin He, and Jun Yang from Harbin Institute of Technology and Tsinghua University, China. From the abstract:

"This paper analyzes the influence of typical external distractions including material, color, distance, lighting, etc. on the depth error of ToF cameras. Our experiments indicated that factors such as lighting, color, material, and distance could cause different influences on the depth error of ToF cameras. However, since the forms of errors are uncertain, it’s difficult to summarize them in a unified law. To further improve the measurement accuracy, this paper proposes an error correction method based on Particle Filter-Support Vector Machine (PF-SVM). Moreover, the experiment results showed that this method can effectively reduce the depth error of ToF cameras to 4.6 mm within its full measurement range (0.5–5 m)."

The authors use Mesa/Heptagon/AMS SR-4000 camera to get their experimental data:

Categories: Imaging, ToF tech news
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