Tracking the full skelet al pose of the hands and fingers is a challenging problem that has a plethora of applications for user interaction. Existing techniques either require wearable hardware, add restrictions to user pose, or require significant computation resources. This research explores a new approach to tracking hands, or any articulated model, by using an augmented rigid body simulation. This allows us to phrase 3D object tracking as a linear complementarity problem with a well-defined solution. Based on a depth sensor's samples, the system generates constraints that limit motion orthogonal to the rigid body model's surface. These constraints, along with prior motion, collision contact constraints, and joint mechanics, are resolved with a projected Gauss-Seidel solver. Due to camera noise properties and attachment errors, the numerous surface constraints are impulse capped to avoid overpowering mechanical constraints. To improve tracking accuracy, multiple simulations are spawned at each frame and fed a variety of heuristics, constraints and poses. A 3D error metric selects the best-fit simulation, helping the system handle challenging hand motions. Such an approach enables real-time, robust, and accurate 3D skelet al tracking of a user's hand on a variety of depth cameras, while only utilizing a single x86 CPU core for processing.
There are many works that focus on gesture recognition @cite_40 . We instead focus on the tracking, noting that gesture is then easily achieved by comparison of the relevant joint orientations from a reference pose or animation. Instead of simply providing collision geometry to a physical environment @cite_41 @cite_2 , we provide knowledge of specific hand and finger pose, with application to gesture recognition.
@cite_41 @cite_40 @cite_2
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Instrumented with a single depth camera, a stereoscopic projector, and a curved screen, MirageTable is an interactive system designed to merge real and virtual worlds into a single spatially registered experience on top of a table. Our depth camera tracks the user's eyes and performs a real-time capture of both the shape and the appearance of any object placed in front of the camera (including user's body and hands). This real-time capture enables perspective stereoscopic 3D visualizations to a single user that account for deformations caused by physical objects on the table. In addition, the user can interact with virtual objects through physically-realistic freehand actions without any gloves, trackers, or instruments. We illustrate these unique capabilities through three application examples: virtual 3D model creation, interactive gaming with real and virtual objects, and a 3D teleconferencing experience that not only presents a 3D view of a remote person, but also a seamless 3D shared task space. We also evaluated the user's perception of projected 3D objects in our system, which confirmed that the users can correctly perceive such objects even when they are projected over different background colors and geometries (e.g., gaps, drops). HoloDesk is an interactive system combining an optical see through display and Kinect camera to create the illusion that users are directly interacting with 3D graphics. A virtual image of a 3D scene is rendered through a half silvered mirror and spatially aligned with the real-world for the viewer. Users easily reach into an interaction volume displaying the virtual image. This allows the user to literally get their hands into the virtual display and to directly interact with an spatially aligned 3D virtual world, without the need for any specialized head-worn hardware or input device. We introduce a new technique for interpreting raw Kinect data to approximate and track rigid (e.g., books, cups) and non-rigid (e.g., hands, paper) physical objects and support a variety of physics-inspired interactions between virtual and real. In particular the algorithm models natural human grasping of virtual objects with more fidelity than previously demonstrated. A qualitative study highlights rich emergent 3D interactions, using hands and real-world objects. The implementation of HoloDesk is described in full, and example application scenarios explored. Finally, HoloDesk is quantitatively evaluated in a 3D target acquisition task, comparing the system with indirect and glasses-based variants.