Qualcomm Announces Snapdragon Spaces XR Developer Platform
Qualcomm. introduces Snapdragon Spaces XR Developer Platform, a headworn Augmented Reality (AR) developer kit to enable the creation of immersive experiences that seamlessly blur the lines between our physical and digital realities. With proven technology and an open, cross-device horizontal platform and ecosystem, Snapdragon Spaces delivers the tools to bring developers' ideas to life and revolutionize the possibilities of headworn AR. Snapdragon Spaces is in early access with select developers and is expected to be generally available in the Spring of 2022.
Qualcomm Technologies is a pioneer in Augmented Reality with over a decade of AR research and development. Utilizing these years of innovation and expertise, Snapdragon Spaces offers robust machine perception technology that is optimized for performance and low power for the next generation of AR glasses. The Snapdragon Spaces platform provides environmental and user understanding capabilities that give developers the tools to create headworn AR experiences that can sense and intelligently interact with the user and adapt to their physical indoor spaces. Some of the marquee environmental understanding features include spatial mapping and meshing, occlusion, plane detection, object and image recognition and tracking, local anchors and persistence, and scene understanding. The user understanding machine perception features include positional tracking and hand tracking.
Qualcomm Technologies is a pioneer in Augmented Reality with over a decade of AR research and development. Utilizing these years of innovation and expertise, Snapdragon Spaces offers robust machine perception technology that is optimized for performance and low power for the next generation of AR glasses. The Snapdragon Spaces platform provides environmental and user understanding capabilities that give developers the tools to create headworn AR experiences that can sense and intelligently interact with the user and adapt to their physical indoor spaces. Some of the marquee environmental understanding features include spatial mapping and meshing, occlusion, plane detection, object and image recognition and tracking, local anchors and persistence, and scene understanding. The user understanding machine perception features include positional tracking and hand tracking.