Article

Technical demonstration on model based training, detection and pose estimation of texture-less 3d objects in heavily cluttered scenes

Authors:

Stefan Hinterstoisser,

Nassir NavabAuthors Info & Claims

ECCV'12: Proceedings of the 12th international conference on Computer Vision - Volume Part III

Pages 593 - 596

https://doi.org/10.1007/978-3-642-33885-4_60

Published: 07 October 2012 Publication History

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Abstract

In this technical demonstration, we will show our framework of automatic modeling, detection, and tracking of arbitrary texture-less 3D objects with a Kinect. The detection is mainly based on the recent template-based LINEMOD approach [1] while the automatic template learning from reconstructed 3D models, the fast pose estimation and the quick and robust false positive removal is a novel addition.

In this demonstration, we will show each step of our pipeline, starting with the fast reconstruction of arbitrary 3D objects, followed by the automatic learning and the robust detection and pose estimation of the reconstructed objects in real-time. As we will show, this makes our framework suitable for object manipulation e.g. in robotics applications.

References

[1]

Hinterstoisser, S., Holzer, S., Cagniart, C., Ilic, S., Konolige, K., Navab, N., Lepetit, V.: Multimodal Templates for Real-Time Detection of Texture-Less Objects in Heavily Cluttered Scenes. In: ICCV (2011).

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Newcombe, R.A., Izadi, S., Hilliges, O., Molyneaux, D., Kim, D., Davison, A.J., Kohli, P., Shotton, J., Hodges, S., Fitzgibbon, A.: KinectFusion: Real-Time Dense Surface Mapping and Tracking. In: ISMAR (2011).

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Anonymous, Authors: Anonymous Title. In: submitted to ACCV (2012).

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Pan, Q., Reitmayr, G., Drummond, T.: ProFORMA: Probabilistic Feature-based On-line Rapid Model Acquisition. In: BMVC (2009).

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Weise, T., Wismer, T., Leibe, B., Van Gool, L.: In-hand Scanning with Online Loop Closure. In: International Workshop on 3-D Digital Imaging and Modeling (2009).

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Newcombe, R.A., Lovegrove, S.J., Davison, A.J.: DTAM: Dense Tracking and Mapping in Real-Time. In: ICCV (2011).

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Technical demonstration on model based training, detection and pose estimation of texture-less 3d objects in heavily cluttered scenes
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision tasks

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Published In

ECCV'12: Proceedings of the 12th international conference on Computer Vision - Volume Part III

October 2012

682 pages

ISBN:9783642338847

Editors:
Andrea Fusiello
Dipartimento di Ingegneria Elettrica, Gestionale e Meccanica (DIEGM), Università degli Studi di Udine, Via delle Scienze, 208, Udine, Italy
,
Vittorio Murino
Dipartimento di Ingegneria Elettrica, Gestionale e Meccanica (DIEGM), IIT Istituto Italiano di Tecnologia, Via Morego 30, Genoa, Italy
,
Rita Cucchiara
Dipartimento di Ingegneria dell'Informazione, Università degli Studi di Modena e Reggio Emilia, Strada Vignolege, 905, Modena, Italy

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Published: 07 October 2012

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Nguyen TVu VNguyen VHoang NVu DTran DPhan KMai ADuong VTran CHo NDuong QNgo PHoang D(2024)Multi Task-Guided 6D Object Pose EstimationProceedings of the 2024 9th International Conference on Intelligent Information Technology10.1145/3654522.3654576(215-222)Online publication date: 23-Feb-2024
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