![]() Let's take a look at this chair as example. We now support the reconstruction of low-texture objects by leveraging the LiDAR Scanner. Our Object Capture system performs best for objects that have sufficient texture details, but we have made further improvements this year. To create a high-quality 3D model, it's important to select an object with good characteristics. Let's first look at the support for more objects with LiDAR. Finally, we will highlight several new enhancements to our model reconstruction capabilities. Then we'll explain how to create an Object Capture flow on iOS with our Object Capture API. Next, we will demonstrate the Guided Capture feature which simplifies data capture for your objects. We will start by introducing the improvements to Object Capture, which now uses LiDAR to support scanning more objects. Now that we have seen a demo of Object Capture on our new sample app, let's move on to all the new exciting features this year. You can also use it as a starting point for creating your own applications. As part of the developer documentation, we provide the source code for this app so that you can download and try it yourself right away. In just a few minutes, a USDZ model will be ready for use. Once scanning for three segments are completed, we'll proceed to the reconstruction stage, which now runs locally on your iOS device. After we finish one orbit, we can flip the object to capture the bottom. We provide the visual guidance on regions where we need more images, along with additional feedback messages to help you capture the best quality shots. Then circle around the object while Object Capture automatically captures the right images for you. ![]() You will see an automatic bounding box generated before you start capturing. First, open the sample app and point it at the object. We will use the sample app to create a 3D model of a beautiful vase in a breeze. Let's take a look at the sample app in action. We also provide a sample app to demonstrate this workflow on iOS. We are now taking a big step to bring the full Object Capture experience to iOS! This means that we can now do both capturing with a user-friendly interface and on-device model reconstruction, all in the palm of your hand. We have received a lot of feedback from you. Since the release of our API for Mac, we have seen many apps leveraging Object Capture to produce high-quality 3D models. These images are transferred to a Mac, where Object Capture API is used to reconstruct a 3D model in a matter of minutes. Object Capture employs cutting-edge computer vision technologies to create a lifelike 3D model from a series of images taken at various angles. Before we get started, let's review what is Object Capture and how it works today. In this session, my colleague Mona and I are going to give you an introduction to Object Capture for iOS. Performance will vary based on system configuration, media type, and other factors.♪ Mellow instrumental hip-hop ♪ ♪ Lei Zhou: Hi, I'm Lei from the Object Capture team. Prerelease Final Cut Pro 10.4.9 with prerelease Canon RAW Plugin 2.0 tested on macOS Catalina, using a 33-second project with Canon Cinema RAW Light video, at 8192x4320 resolution and 29.97 frames per second (as part of a transcode test). Mac Pro systems tested with an attached Pro Display XDR. ![]() Testing conducted by Apple in August 2020 using 2.5GHz 28-core Intel Xeon W-based Mac Pro systems with 384GB of RAM and dual AMD Radeon Pro Vega II graphics with Infinity Fabric Link and 32GB of HBM2 each, configured with 4TB SSD as well as 2.4GHz 8-core Intel Core i9-based 16-inch MacBook Pro systems with 64GB of RAM and Radeon Pro 5600M graphics with 8GB of HBM2, configured with 8TB SSD.Performance will vary based on system configuration, media type, and other factors. Prerelease Final Cut Pro 10.4.9 with prerelease plugins from RED Apple Workflow Installer v16, and Final Cut Pro 10.4.8 with plugins from RED Apple Workflow Installer v15 tested on macOS Catalina, using an 11-second project with REDCODE® RAW 4:1 video, at 8192x4320 resolution and 23.98 frames per second, transcoded to Apple ProRes 422.
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