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Time-of-Flight Guidebook 2.0: Design tips to boost 3D performance and cut integration time & cost

time-of-Flight Guidebook 2.0 LUCID Helios2

Have you wondered how to boost the performance of your 3D Time-of-Flight imaging application and at the same time cut your integration time and cost? Our hands-on guidebook describes how you can optimize the benefits of Time-of-Flight by considering various factors such as the environment of the application and the target object properties in the scene. See also how the various Helios2 models solve common 3D application challenges.

What’s Inside:

• Outdoors vs Controlled Environments
• Target & Camera Motion
• Specular, Diffuse & Transparent Targets
• Scene Complexity Simplified
• Working Distance Considerations
• Expanding Functionality
• Put It All Together

Time of Flight Guidebook – PDF Download
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– Sample Chapter –

SPECULAR, DIFFUSE & TRANSPARENT TARGETS ToF works best on targets with surfaces that have neither high specular reflection (i.e., mirror-like) nor absorbent non-reflective surfaces. Both extremes lead to point cloud distortions. For example, black PVC piping has both low reflectivity (black color) and highly specular surfaces, creating both voids and spikes in the point cloud (Image Set 4, Example c.) Targets that are black or very dark will absorb light and thus return the least amount of light creating voids or holes in the point cloud. Targets with high specular reflections can saturate pixels creating spikes in the point cloud that are closer in distance than their true position. Targets with these properties may not be suitable for ToF. Targets with diffuse surfaces and high reflectivity work best for ToF (Image Set 4, Example a, b, d). These targets send enough light back to the ToF sensor without specular reflections. Some objects however, exhibit properties that are less than ideal but are still discernible within the scene. In these situations, it is possible to increase target details via changes in exposure time and gain, image accumulation, and filtering. Determining the best exposure time maximizes usable depth data for both high- and low-reflectivity targets. The Helios2 camera models enables three discrete exposure time presets as well as high and normal gain settings. Longer exposure times and high gain should be used for scenes further from the camera, or when imaging objects with low reflectivity. Shorter exposure time and normal gain is used for scenes closer to the camera, or objects that appear over saturated. EXPOSURE TIME AND GAIN IMAGE ACCUMULATION The Helios2 processing pipeline is capable of accumulating multiple frames for improved depth calculations. This is helpful for targets that produce noisy data. With image accumulation, depth frames are averaged over a set number of frames, improving imaging results. It should be noted that the higher the number of frames accumulated, the slower the depth data generation, as more images must be captured to calculate the data. CONFIDENCE THRESHOLD Depth data confidence is based on a level of intensity for each point. If a returning signal is too weak, there is low confidence in the resulting depth data. Thresholding removes depth data with low intensity/confidence, improving scene clarity. SPATIAL FILTERING Spatial filtering reduces noise by adjusting and averaging depth data differences between neighboring pixels—smoothing out surfaces. Additionally, the Helios camera also uses edge-preservation in its spatial filtering, reducing noise in surfaces while maintaining object-edge sharpness. The Helios2 processing pipeline is capable of accumulating multiple frames for improved depth calculations. This is helpful for targets that produce noisy data. With image accumulation, depth frames are averaged over a set number of frames, improving imaging results. It should be noted that the higher the number of frames accumulated, the slower the depth data generation, as more images must be captured to calculate the data. HIGH DYNAMIC RANGE (HDR) MODE: HELIOS2+ Time-of-Flight Guidebook 2.0 - 3D Helios2 Camera

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