Prof. Dr. Didier Stricker

Dr. Alain Pagani

Keonna Cunningham

Dr. Oliver Wasenmüller

Dr. Gabriele Bleser

Dr. Bruno Mirbach

Dr. Jason Raphael Rambach

Dr. Bertram Taetz

Dr. Muhammad Zeshan Afzal

Mhd Rashed Al Koutayni

Jilliam Maria Diaz Barros

Mahdi Chamseddine

Steve Dias da Cruz

Ahmet Firintepe

Sophie Folawiyo

David Michael Fürst

Kamalveerkaur Garewal

Christiano Couto Gava

Leif Eric Goebel

Tewodros Amberbir Habtegebrial

Jigyasa Singh Katrolia

Andreas Kölsch

Onorina Kovalenko

Muhammad Jameel Nawaz Malik

Nareg Minaskan Karabid

Mohammad Minouei

Manthan Pancholi

Engr. Kumail Raza

Dr. Nadia Robertini

María Alejandra Sánchez Marín

Dr. Kripasindhu Sarkar

Alexander Schäfer

Pascal Schneider

Lukas Stefan Staecker

Dr. Vladislav Golyanik

Dr. Aditya Tewari

André Luiz Brandão

Reality Filtering: A Visual Time Machine in Augmented Reality

Reality Filtering: A Visual Time Machine in Augmented Reality
Michael Zoellner, Alain Pagani, Yulian Pastarmov, Harald Wuest, Didier Stricker
Proceedings of the 9th International Symposium on Virtual Reality, Archaeology and Cultural Heritage International Symposium on Virtual Reality, Archaeology and Cultural Heritage (VAST-08), December 2-5, Braga, Portugal

Abstract:: We present Reality Filtering, an application that makes it possible to visualize original content like drawings or paintings of buildings and frescos seamlessly superimposed on reality by using filtered augmented reality. This enables simple and inexpensive applications in the cultural heritage and architecture area. The main idea is that the video stream showing the reality is filtered on the fly to acquire the same presentation style as the virtual objects. This allows for a better integration of original historic content and creates the impression of a virtual time journey. The registration of the virtual objects in the video images is provided by a robust 6DOF tracking framework based on two technologies that work in tandem: an initialization step based on Randomized Trees and a frame-to-frame tracking phase based on KLT. For the initialization, we present the novel concept of temporally distributed computational load (TDCL), which is able to automatically detect and register multiple objects while maintaining a constant video frame rate of 20 frames / sec. For mid- to long-range augmentation a pure 2- dimensional tracking with 3DOF is applicable and leads to significant performance gain. The entire application runs in real time on Ultra Mobile PCs.

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