![]() The solution is based on the ARTag technology utilizing specific markers printed on a band, which should be worn on a user’s wrist in place of a watch in order to start a virtual try-on the watch. ![]() Virtual Try-on WatchesĪ good example of virtual watches try-on is the AR-Watches app allowing users to try on various watches. Let’s review how some of these solutions work under the hood. The virtual fitting room technology market provides offerings for accessories, watches, glasses, hats, clothes, and others. Thus, it’s recommended to involve data scientists for developing a custom pose estimation model supposed to detect keypoints on only one or two feet in the frame and operate in real-time. The conclusion was that virtual fitting room apps might require additional functionality along with the standard AR libraries. It is exactly the case of a footwear fitting room when the algorithm is supposed to process only a person’s legs. Since this algorithm is aimed to identify the whole body, it doesn’t detect any keypoints if the processed image contains only a part of the body. One more issue was the poor identification of body parts by the ARKit algorithm. The cause of this limitation may be the maintenance of the inference speed while neglecting the tracking accuracy, which might be critical for apps working in real-time. As you can see from the video above, the tracking accuracy is too low to use it for footwear positioning. When working with ARKit (Augmented Reality framework for Apple’s devices) we discovered that it has rendering limitations. Read also: Human Pose Estimation Technology Capabilities and Use Cases in 2022 Utilization of ARKit for 3D human body pose estimation and 3D model rendering
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