New Leap Motion 2 Brings High-Finish Hand-Tracking To Standalone Headsets > 자유게시판

Years earlier than the trendy era of VR, Leap Motion set out to build a hand-monitoring module that it hoped would revolutionize human-computer interaction. Launched initially in 2013, the device was praised for its impressive hand-monitoring, however failed to discover a killer use-case when used as an accessory for PCs. But because the VR spark started anew just a few years later, Leap Motion’s hand-monitoring started to look like a perfect enter technique for interacting with immersive content. Between then and now the corporate pivoted closely into the VR space, but didn’t handle to seek out its way into any major headsets until effectively after the launch of first-gen VR headsets like Oculus Rift and HTC Vive (although that didn’t cease builders from attached the Leap Motion module and iTagPro bluetooth tracker experimenting with hand-monitoring). Through the years the corporate stored honing their hand-monitoring tech, improving its software stack which made hand-monitoring with the primary era of the hand-monitoring module higher over time. More just lately the corporate has constructed newer variations of its hand-monitoring module-together with integrations with headsets from the likes of Varjo and Lynx-but never sold that newer hardware as a standalone tracking module that anybody could buy.

Leap Motion 2 is the primary new standalone hand-tracking module from the corporate since the unique, and ItagPro it’s already available for pre-order, priced at $140, and expected to ship this Summer. Purportedly constructed for "XR, desktop use, holographic shows, and Vtubing," Ultraleap says the Leap Motion 2 is its "most flexible digicam ever" because of help for Windows, MacOS, and standalone Android headsets with Qualcomm’s XR2 chip. Ultraleap says that Leap Motion 2 will give builders an easy way to experiment with high-high quality hand-monitoring by adding it to headsets like Varjo Aero, Pico Neo 3 Pro, and Lenovo’s ThinkReality VRX. The corporate additionally plans to promote a mount for the device to be attached to XR headsets, as it did with the original machine. And with the launch of this next-gen hand-tracking module, Ultraleap says it’s moving on from the original Leap Motion iTagPro bluetooth tracker. Gemini for ItagPro macOS. Support can even proceed to be offered. Future variations of the software program will not ship any performance improvements to the unique Leap Motion Controller system," the company says.

Object detection is widely utilized in robot navigation, intelligent video surveillance, industrial inspection, aerospace and many other fields. It is a crucial branch of image processing and laptop imaginative and prescient disciplines, and can also be the core a part of clever surveillance systems. At the identical time, goal detection can also be a fundamental algorithm in the sphere of pan-identification, which plays a significant role in subsequent duties such as face recognition, gait recognition, crowd counting, and instance segmentation. After the primary detection module performs target detection processing on the video body to obtain the N detection targets in the video body and the primary coordinate info of every detection target, the above method It also consists of: displaying the above N detection targets on a display screen. The first coordinate data corresponding to the i-th detection goal; acquiring the above-talked about video frame; positioning within the above-talked about video body in accordance with the primary coordinate info corresponding to the above-mentioned i-th detection target, obtaining a partial image of the above-talked about video body, and determining the above-talked about partial image is the i-th picture above.

The expanded first coordinate data corresponding to the i-th detection target; the above-talked about first coordinate information corresponding to the i-th detection goal is used for positioning in the above-talked about video body, together with: in line with the expanded first coordinate data corresponding to the i-th detection goal The coordinate information locates within the above video body. Performing object detection processing, if the i-th image consists of the i-th detection object, buying place info of the i-th detection object within the i-th picture to obtain the second coordinate info. The second detection module performs goal detection processing on the jth picture to determine the second coordinate info of the jth detected target, where j is a positive integer not greater than N and never equal to i. Target detection processing, acquiring a number of faces in the above video frame, and first coordinate data of each face; randomly obtaining target faces from the above multiple faces, and intercepting partial photos of the above video body based on the above first coordinate information ; performing goal detection processing on the partial picture by the second detection module to obtain second coordinate info of the target face; displaying the target face based on the second coordinate info.