Zivid SDK 2.9 Preview: Sharper Point Clouds, Faster Capture, Easy Development

By Bhalchandra Chorghade, Editor, CNCTimes.com

Zivid SDK 2.9 preview is now available. Come check out the wide range of features we have managed to fit into one easy to use package. To memory, this is our biggest, fullest coverage release to date. It is packed with features that will really make a difference in your 3D point cloud quality, ease of use and your system’s performance. So, let’s dive in and take a look at all of the additions.

Pristine and complete point clouds

The ideal 3D camera is the one that returns a point cloud that is as true to reality as possible. Who doesn’t want to see exactly the same thing they see with their own eyes? With every new SDK release point cloud quality is always front of our minds, we tirelessly aim to provide a point cloud that can come closer and closer to meeting this ideal of ‘true-to-reality’.

In this SDK we’ve improved and added to our 3D filter stack which now does a far better job at suppressing noise and removing false points and clusters in the point cloud that shouldn’t be there, while still preserving small features.

Developer simplicity – High complexity, simply accessible

This pursuit is straightforward in concept, but much harder to achieve in practice. As Einstein was rumored to have said: ‘Any intelligent fool can make things bigger and more complex, it takes a touch of genius to move in the opposite direction. Things should be as simple as possible, and no simpler’.

We’re with Albert on this one. There is a great deal of complexity living inside a 3D camera or sensor, much of it very specialized in nature. The Zivid approach is that you can be fresh in the field of 3D vision and still be able to get superb point clouds from a Zivid camera. Zivid Studio features map directly to the API, so that what you see and do in the UI visually, you can do programmatically with the API. We realized, sometimes you need to go the other way as well. In this SDK we worked to ensure that we provide improved functionality through the API and to Zivid Studio to make your development a breeze.

Faster, reliable capture times

We are continuing where we left off in our previous SDK release with further optimization of the acquisition and processing execution for faster captures with more reliable and precise timing that you can take advantage of.

New point cluster filter

• Improved smoothing filter (with better edge preservation)

• New presets for camera settings (in Zivid SDK and Zivid Studio)

• New region-of-interest filters (box and distance)

• The capture function now returns when camera acquisition is complete

• Added infield camera correction tool in Zivid Studio

• 10% improvement to capture speed

Benefit Feature

• Pristine and complete point clouds Cluster filter

• Smoothing filter

• Camera pre-sets in Zivid SDK/Studio

• Developer simplicity Camera pre-sets in Zivid SDK/Studio

• Region-of-interest filter

• File cameras in Zivid Studio for all models

• Faster, reliable captures functions return as soon as camera acquisition is complete

• Region-of-interest filter

• 10% speed improvement

Cluster Filter

The cluster filter is the newest addition to the filters in Zivid’s artifact reduction technology suite. This filter complements other filters such as the reflection filter and the outlier filter. The cluster filter identifies groupings of anomalous points that are not part of any object in the scene. These unwanted points are a frequent byproduct of capturing objects made of highly reflective materials, think shiny chrome cylinders, or plastic film wrap over new items, and you know what we mean.

The cluster filter will reduce ambiguity and help improve matching precision for CAD matching and other pose estimation algorithms. The cluster filter will also increase the success rate of path planning algorithms by eliminating potential false positive collision checks that are triggered by floating points. This will increase the number of approaches and picking positions the robot can reliably make. In total, the cluster filter will improve the success rate of your picking solution by yielding higher precision pose estimation with higher chance of using the optimal approach path.

https://blog.zivid.com/zivid-sdk-2.9-preview

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