Mobile devices with passive depth sensing capabilities are ubiquitous, and recently active depth sensors have become available on some tablets and AR/VR devices. Although real-time depth data is accessible, its rich value to mainstream AR applications has been sorely under-explored. Adoption of depth-based UX has been impeded by the complexity of performing even simple operations with raw depth data, such as detecting intersections or constructing meshes. In this paper, we introduce DepthLab, a software library that encapsulates a variety of depth-based UI/UX paradigms, including geometry-aware rendering (occlusion, shadows), surface interaction behaviors (physics-based collisions, avatar path planning), and visual effects (relighting, 3D-anchored focus and aperture effects). We break down the usage of depth into localized depth, surface depth, and dense depth, and describe our real-time algorithms for interaction and rendering tasks. We present the design process, system, and components of DepthLab to streamline and centralize the development of interactive depth features. We have open-sourced our software at https://github.com/googlesamples/arcore-depth-lab to external developers, conducted performance evaluation, and discussed how DepthLab can accelerate the workflow of mobile AR designers and developers. With DepthLab we aim to help mobile developers to effortlessly integrate depth into their AR experiences and amplify the expression of their creative vision.

Augmented reality (AR) for smartphones has matured from a technology for earlier adopters, available only on select high-end phones, to one that is truly available to the general public. One of the key breakthroughs has been in low-compute methods for six degree of freedom (6DoF) tracking on phones using only the existing hardware (camera and inertial sensors). 6DoF tracking is the cornerstone of smartphone AR allowing virtual content to be precisely locked on top of the real world. However, to really give users the impression of believable AR, one requires mobile depth. Without depth, even simple effects such as a virtual object being correctly occluded by the real-world is impossible. However, requiring a mobile depth sensor would severely restrict the access to such features. In this article, we provide a novel pipeline for mobile depth that supports a wide array of mobile phones, and uses only the existing monocular color sensor. Through several technical contributions, we provide the ability to compute low latency dense depth maps using only a single CPU core of a wide range of (medium-high) mobile phones. We demonstrate the capabilities of our approach on high-level AR applications including real-time navigation and shopping.