ISMAR Papers for Session "Reconstruction and Fusion"
Reconstruction and Fusion
Session :
Reconstruction and Fusion
Date & Time : September 11 10:00 am - 12:45 pm Location : HS1 Chair : Walterio Mayol-Cuevas, Bristol University Papers :
Improved Registration for Vehicular AR using Auto-Harmonization
Authors: Eric Foxlin, Thomas Calloway, Hongsheng Zhang
Abstract : This paper describes the design, development and testing of an AR system that
was developed for aerospace and ground vehicles to meet stringent accuracy
and robustness requirements. The system uses an optical see-through HMD, and
thus requires extremely low latency, high tracking accuracy and precision
alignment and calibration of all subsystems in order to avoid
mis-registration and “swim”. The paper focuses on the optical/inertial
hybrid tracking system and describes novel solutions to the challenges with
the optics, algorithms, synchronization, and alignment with the vehicle and
HMD systems. A system accuracy analysis is presented with simulation results
to predict the registration accuracy. Finally, a car test is used to create a
through-the-eyepiece video demonstrating well-registered augmentations of the
road and nearby structures while driving.
Real-Time Illumination Estimation from Faces for Coherent Rendering
Authors: Sebastian B. Knorr, Daniel Kurz
Abstract : We present a method for estimating the real-world lighting conditions within
a scene in real-time. The estimation is based on the visual appearance of a
human face in the real scene captured in a single image of a monocular
camera. In hardware setups featuring a user-facing camera, an image of the
user's face can be acquired at any time. The limited range in variations
between different human faces makes it possible to analyze their appearance
offline, and to apply the results to new faces. Our approach uses radiance
transfer functions - learned offline from a dataset of images of faces under
different known illuminations - for particular points on the human face.
Based on these functions, we recover the most plausible real-world lighting
conditions for measured reflections in a face, represented by a function
depending on incident light angle using Spherical Harmonics. The pose of the
camera relative to the face is determined by means of optical tracking, and
virtual 3D content is rendered and overlaid onto the real scene with a fixed
spatial relationship to the face. By applying the estimated lighting
conditions to the rendering of the virtual content, the augmented scene is
shaded coherently with regard to the real and virtual parts of the scene. We
show with different examples under a variety of lighting conditions, that our
approach provides plausible results, which considerably enhance the visual
realism in real-time Augmented Reality applications.
Comprehensive Workspace Calibration for Visuo-Haptic Augmented Reality
Authors: Ulrich Eck, Frieder Pankratz, Christian Sandor, Gudrun Klinker, Hamid Laga
Abstract : Visuo-haptic augmented reality systems enable users to see and touch digital
information that is embedded in the real world. Precise co-location of
computer graphics and the haptic stylus is necessary to provide a realistic
user experience. PHANToM haptic devices are often used in such systems to
provide haptic feedback. They consist of two interlinked joints, whose angles
define the position of the haptic stylus and three sensors at the gimbal to
sense its orientation. Previous work has focused on calibration procedures
that align the haptic workspace within a global reference coordinate system
and developing algorithms that compensate the non-linear position error,
caused by inaccuracies in the joint angle sensors. In this paper, we present
an improved workspace calibration that additionally compensates for errors in
the gimbal sensors. This enables us to also align the orientation of the
haptic stylus with high precision. To reduce the required time for
calibration and to increase the sampling coverage, we utilize time-delay
estimation to temporally align external sensor readings. This enables users
to continuously move the haptic stylus during the calibration process, as
opposed to commonly used point and hold processes. We conducted an evaluation
of the calibration procedure for visuo-haptic augmented reality setups with
two different PHANToMs and two different optical trackers. Our results show a
significant improvement of orientation alignment for both setups over the
previous state of the art calibration procedure. Improved position and
orientation accuracy results in higher fidelity visual and haptic
augmentations, which is crucial for fine-motor tasks in areas including
medical training simulators, assembly planning tools, or rapid prototyping
applications. A user friendly calibration procedure is essential for
real-world applications of VHAR.
Recognition and reconstruction of transparent objects for Augmented Reality
Authors: Alan Francisco Torres-Gomez, Walterio Mayol-Cuevas
Abstract : Dealing with real transparent objects for AR is challenging due to their lack
of texture and visual features as well as the drastic changes in appearance
as the background, illumination and camera pose change. The few existing
methods for glass object detection usually require a carefully controlled
environment, specialized illumination hardware or ignore information from
different viewpoints. In his work, we explore the use of a learning approach
for classifying transparent objects from multiple images with the aim of both
discovering such objects and building a 3D reconstruction to support
convincing augmentations. We extract, classify and group small image patches
using a fast graph-based segmentation and employ a probabilistic formulation
for aggregating spatially consistent glass regions. We demonstrate our
approach via analysis of the performance of glass region detection and
example 3D reconstructions that allow virtual objects to interact with them.