Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.263269
Title: Adaptive motion analysis in machine and biological vision
Author: Clifford, Colin Walter Giles
ISNI:       0000 0001 3559 0539
Awarding Body: University of London
Current Institution: University College London (University of London)
Date of Award: 1997
Availability of Full Text:
Access from EThOS:
Full text unavailable from EThOS. Please try the link below.
Access from Institution:
Abstract:
This thesis investigates the problem of machine and biological motion perception from an adaptive systems perspective. Adaptive temporal filters are incorporated into two established image motion analysis algorithms, one each from machine and biological vision. The correlation-based Reichardt detector (Reichardt, 1961) is equipped with adaptive filters to account for existing electrophysiological data on motion adaptation in the insect lobula plate. The wider applicability of the model is tested by recording electrophysiologically from cells in the mammalian nucleus of the optic tract (NOT), and by investigating rapid adaptation to motion in human psychophysical observers. Adaptive temporal filters are also used to implement a phase-based scheme for image velocity measurement (Fleet and Jepson, 1989). The use of adaptive filters reduces the computational load of the phase-based scheme while maintaining performance on a synthetic test sequence. The adaptive scheme shows an advantage over its non-adaptive counterpart at high levels of noise as adaptation serves to maximise the signal power in the output of the filters.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.263269  DOI: Not available
Keywords: Biological motion; Adaptive filters
Share: