Back projection algorithm for line structured light extraction

Structure from motion and structure from light are usually regarded separately. To combine both methods, using the same images to retrieve three dimensional information about the environment, both methods must work side by side without interfering each other. This research work describes how laser line patterns can be extracted from images while being robust to scattering media and ambient light.

[1]  Joaquim Salvi,et al.  Laser stripe peak detector for 3D scanners. A FIR filter approach , 2004, ICPR 2004.

[2]  James R. Bergen,et al.  Visual odometry , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..

[3]  Yonghuai Liu,et al.  Practical issues and development of underwater 3D laser scanners , 2010, 2010 IEEE 15th Conference on Emerging Technologies & Factory Automation (ETFA 2010).

[4]  Robert B. Fisher,et al.  A Comparison of Algorithms for Subpixel Peak Detection , 1996 .

[5]  Shree K. Nayar,et al.  Structured light in scattering media , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.

[6]  Marc Hildebrandt,et al.  Adaptive AUV mission management in under-informed situations , 2010, OCEANS 2010 MTS/IEEE SEATTLE.

[7]  Josef Kittler,et al.  Curvature scale space image in shape similarity retrieval , 1999, Multimedia Systems.

[8]  L. Brignone,et al.  First sea trials of a laser aided three dimensional underwater image mosaicing technique , 2011, OCEANS 2011 IEEE - Spain.

[9]  Kenichi Asakawa,et al.  Optimization of Configuration of Autonomous Underwater Vehicle for Inspection of Underwater Cables , 1997 .

[10]  Luc Van Gool,et al.  Speeded-Up Robust Features (SURF) , 2008, Comput. Vis. Image Underst..

[11]  G E Packard,et al.  Hull inspection and confined area search capabilities of REMUS autonomous underwater vehicle , 2010, OCEANS 2010 MTS/IEEE SEATTLE.

[12]  Srinivasa G. Narasimhan,et al.  A low-power structured light sensor for outdoor scene reconstruction and dominant material identification , 2012, 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops.

[13]  Andrew Zisserman,et al.  N-View Computational Methods , 2004 .

[14]  Antoni Burguera,et al.  Imaging Systems for Advanced Underwater Vehicles , 2011 .

[15]  G.G. Acosta,et al.  Low-cost Autonomous Underwater Vehicle for pipeline and cable inspections , 2007, 2007 Symposium on Underwater Technology and Workshop on Scientific Use of Submarine Cables and Related Technologies.

[16]  Hideo Saito,et al.  Calibration of a structured light system by observing planar object from unknown viewpoints , 2008, 2008 19th International Conference on Pattern Recognition.

[17]  Donna M. Kocak,et al.  A Focus on Recent Developments and Trends in Underwater Imaging , 2008 .

[18]  K. Hamilton,et al.  Subsea pilotless inspection using an autonomous underwater vehicle (SPINAV): concepts and results , 2005, Europe Oceans 2005.

[19]  Francisco Angel Moreno,et al.  ERODE: An efficient and robust outlier detector and its application to stereovisual odometry , 2013, 2013 IEEE International Conference on Robotics and Automation.