Dr Philip Culverhouse
Profiles

Dr Philip Culverhouse

Associate Professor in Computer Vision & Robotics

School of Computing, Electronics and Mathematics (Faculty of Science and Engineering)

Qualifications

University of York: BA (hons) (Biology) 1977

University of Sussex: M.Phil. (Engineering) 1988

University of Plymouth: Ph.D. (Engineering) 1994

Teaching interests

 

VLSI design, VHDL, Computer Vision, Design and Problem Solving. ALSO vision guidance for robot football see: Plymouth University Robot Football Facebook page

Research interests

Natural Object Categorisation, Machine vision, Expert performance, in situ plankton recognition


Recent publications:

1)     1)   A. Mohamed, P. F. Culverhouse, A. Cangelosi, and C.Yang, (2018, in press) Design and Implement a Cognitive Model for Active StereoPlatform for Tomato Detection, IEEE Access.

2)   A. Mohamed, P. F. Culverhouse, A. Cangelosi, and C.Yang, (2018, in press) Vergence Controller Based Feature Detection, IEEE Access.

3)   A. Mohamed, P. F. Culverhouse, A. Cangelosi, and C.Yang, (2018, in press) Vergence Controller Based Pyramid NormalizationCross-Correlation, IEEE Access.

4)   A. Mohamed, P. F. Culverhouse, A. Cangelosi, and C.Yang, (2018) Active Stereo Platform: Online Epipolar Geometry Update,” EURASIPJ. Image Video Process., vol. 2018:54, no. 1687–5281, p. 16, 2018.A.

 

5)   Pitois SG, Tilbury J, Bouch P, Close, H, Barnett S andCulverhouse, PF (2018) Comparison of a Cost-Effective Integrated PlanktonSampling and Imaging Instrument with Traditional Systems for MesozooplanktonSampling in the Celtic Sea. Frontiers in Marine Science 5, 9 pages, DOI=10.3389/fmars.2018.00005.

 

6)   Allsop T, Lee GB, Wang C, Neal R, Kalli K, CulverhouseP and Webb DJ (2018)

Laser-sculpted hybrid photonic magnetometer withnanoscale magnetostrictive interaction. Sensors and Actuators A: Physical, 269,pp.545. doi.org/10.1016/j.sna.2017.12.021.

7)   Allsop T, Kundrat V, Kalli K, Lee GB, Neal, Bond P, ShiB, Sullivan J,  P Culverhouse and Webb DJ(2018) Methane detection scheme based upon the changing optical constants of azinc oxide/platinum matrix created by a redox reaction and their effect uponsurface plasmons. Sensors and Actuators B: Chemical 255, 843 – 853. doi={https://doi.org/10.1016/j.snb.2017.08.058.

8)   Mohamed A., P. F. Culverhouse, R. De Azambuja, A.Cangelosi, and C. Yang, (2017) Automating Active Stereo Vision CalibrationProcess with Cobots,” IFAC-PapersOnLine, vol. 50, no. 2, pp. 163–168, Dec.2017.

 

9)   Shafait F, Harvey ES, Shortis MR, Mian A,Ravanbakhsh, M, Seager JW, Culverhouse PF, Cline DE, and Edgington DR (2017)Towards automating underwater measurement of fish length: a comparison ofsemi-automatic and manual stereo–video measurements. – ICES Journal of MarineScience, doi:10.1093/icesjms/fsx007. 

Research groups

  • Robotics and Intelligent Systems Lab

Links

  • RAPID website: https://www.facebook.com/Research-on-Automated-Plankton-Identification-141817862551413
  • SCOR WG130 web site: http://www.scor-wg130.net/