TUTCRIS - Tampereen teknillinen yliopisto

TUTCRIS

A Speed-optimized RGB-Z capture system with improved denoising capabilities

Tutkimustuotosvertaisarvioitu

Yksityiskohdat

AlkuperäiskieliEnglanti
OtsikkoIS&T/SPIE Image Processing: Algorithms and Systems XII, 3-5.2.2014, San Francisco, California, USA
ToimittajatKaren O. Egiazarian, Sos S. Agaian, Atanas P. Gotchev
JulkaisupaikkaCalifornia, USA
KustantajaS P I E - International Society for Optical Engineering
Sivut1-13
Sivumäärä13
ISBN (painettu)978-0-8194-9936-3
DOI - pysyväislinkit
TilaJulkaistu - 2014
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
TapahtumaSPIE CONFERENCE PROCEEDINGS -
Kesto: 1 tammikuuta 1900 → …

Julkaisusarja

NimiProceedings of SPIE
Vuosikerta9019
ISSN (painettu)0277-786X
ISSN (elektroninen)1996-756X

Conference

ConferenceSPIE CONFERENCE PROCEEDINGS
Ajanjakso1/01/00 → …

Tiivistelmä

We have developed an end-to-end system for 3D scene sensing which combines a conventional high-resolution RGB
camera with a low-resolution Time-of-Flight (ToF) range sensor. The system comprises modules for range data denoising, data re-projection and non-uniform to uniform up-sampling and aims at composing high-resolution 3D video
output for driving auto-stereoscopic 3D displays in real-time. In our approach, the ToF sensor is set to work with short integration time with the aim to increase the capture speed and decrease the amount of motion artifacts. However, reduced integration time leads to noisy range images. We specifically address the noise reduction problem by performing a modification of the non-local means filtering in spatio-temporal domain. Time-consecutive range images are utilized not only for efficient de-noising but also for accurate non-uniform to uniform up-sampling on the high-resolution RGB grid. Use is made of the reflectance signal of the ToF sensor for providing a confidence-type of feedback to the denosing module where a new adaptive averaging is proposed to effectively handle motion artifacts. As of the non-uniform to uniform resampling of range data is concerned, we have developed two alternative solutions; one relying entirely on the GPU power and another being applicable to any general platform. The latter method employs an intermediate virtual range camera recentering after with the resamploing process degrades to a 2D interpolation performed within the lowresolution grid. We demonstrate a real-time performance of the system working in low-power regime.

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