IEEE ISMAR 2012 Workshop on Tracking Methods and Applications (TMA)


The focus of this workshop is on presenting, discussing and demonstrating recent tracking methods and applications that work well in practice and that show some superiority over state-of-the-art methods. Rather than focusing on pure novelty, this workshop encourages presentations that concentrate on complete systems and integrated approaches.

The TMA workshop looks at pose tracking from an end-to-end point of view. Practical tracking solutions for AR are usually complex systems that combine many methods including, but not limited to:

Two keynote talks given by invited world-renowned specialists in fields from which Augmented Reality can highly benefit will be delivered at the beginning of the presentation sessions. The fields include computer vision, other sensing modalities (e.g. GPS, inertial, etc.) and systems issues (calibration, estimation, fusion, etc.).

Date and Location

Monday, November 5, 9:00 - 17:30

Georgia Tech Hotel and Conference Center


09:15Invited speaker: Andrew Davison
slidesHow Increasing Frame-Rate Improves Real-Time Tracking
  Higher frame-rates promise better tracking of rapid motion, but advanced real-time vision systems rarely exceed the standard 10-60Hz range, arguing that the computation required would be too great. Actually, increasing frame-rate is mitigated by reduced computational cost per frame in trackers which take advantage of prediction. Additionally, when we consider the physics of image formation, high frame-rate implies that the upper bound on shutter time is reduced, leading to less motion blur but more noise. So, putting these factors together, how are application-dependent performance requirements of accuracy, robustness and computational cost optimised as frame-rate varies? Using 3D camera tracking as our test problem, and analysing a fundamental dense whole image alignment approach, we open up a route to a systematic investigation via the careful synthesis of photorealistic video using ray-tracing of a detailed 3D scene, experimentally obtained photometric response and noise models, and rapid camera motions. Our multi-frame-rate, multi-resolution, multi-light-level dataset is based on tens of thousands of hours of CPU rendering time. Our experiments lead to quantitative conclusions about frame-rate selection and highlight the crucial role of full consideration of physical image formation in pushing tracking performance.
10:00Yuji Oyamada
Single Camera Calibration using partially visible calibration objects based on Random Dots Marker Tracking Algorithm
Steve Bourgeois
paperA mobile markerless Augmented Reality system for the automotive field
11:00Coffee break
11:15Markus Miezal
Towards practical inside-out head tracking for mobile seating bucks
Koji Makita
Virtualized reality model-based benchmarking of AR/MR camera tracking methods
12:15Lunch break
14:00Invited speaker: Jan-Michael Frahm
 Fast and Scalable Crowd Sourced Image Registration and Dense Reconstruction of the World
  In recent years photo and video sharing web sites like Flickr and YouTube have become increasingly popular. Nowadays, every day millions of photos are uploaded. These photos survey the world. Given the scale of data we are facing significant challenges to process them within a short time frame given limited resources. In my talk I will present our work on the highly efficient organization and reconstruction of 3D models from city scale photo collections (millions of images per city) on a single PC in the span of a day. The approaches address a variety of the current challenges to achieve a concurrent 3D model from these data. For registration and reconstruction from photo collections these challenges are: selecting the data of interest from the noisy datasets, and efficient robust camera motion estimation. Shared challenges of photo collection based 3D modeling and 3D reconstruction from video are: high performance stereo estimation from multiple views, as well as image based location recognition for topology detection. In the talk I will discuss the details of our image organization method, our efficient stereo fusion technique for determining the scene depths from photo collection images.
14:45Daniel Wagner
slidesHardware and Software Trends in Mobile AR
15:15Breakout Session
 Participants will form small groups to separately discuss advances/ limitations/requirements of topics such as RGB-D camera-based tracking, tracking in outdoor environment, parallel/simultaneous tracking and reconstruction, tracking on mobile devices, sensor fusion, etc.
16:00Coffee break
16:15Reports and discussions for breakouts
 One representative of each break-out group will report on the discussion
16:45Demo Session
 Demos from presenters and participants
17:30End of the workshop


Participation is open to all attendees registering for the workshop, not only to presenters. We explicitly invite non-research attendees to join us as well and provide valuable insight into commercial areas of interest and constraints.

Keynote Speakers

Workshop Organizers and Program Committee


The workshop organizers can be reached via e-mail at