Performance of visually guided tasks using simulated prosthetic vision and saliency-based cues

OBJECTIVE The objective of this paper is to evaluate the benefits provided by a saliency-based cueing algorithm to normally sighted volunteers performing mobility and search tasks using simulated prosthetic vision. APPROACH Human subjects performed mobility and search tasks using simulated prosthetic vision. A saliency algorithm based on primate vision was used to detect regions of interest (ROI) in an image. Subjects were cued to look toward the directions of these ROI using visual cues superimposed on the simulated prosthetic vision. Mobility tasks required the subjects to navigate through a corridor, avoid obstacles and locate a target at the end of the course. Two search task experiments involved finding objects on a tabletop under different conditions. Subjects were required to perform tasks with and without any help from cues. RESULTS Head movements, time to task completion and number of errors were all significantly reduced in search tasks when subjects used the cueing algorithm. For the mobility task, head movements and number of contacts with objects were significantly reduced when subjects used cues, whereas time was significantly reduced when no cues were used. The most significant benefit from cues appears to be in search tasks and when navigating unfamiliar environments. SIGNIFICANCE The results from the study show that visually impaired people and retinal prosthesis implantees may benefit from computer vision algorithms that detect important objects in their environment, particularly when they are in a new environment.

[1]  Daniel Palanker,et al.  Design of a high-resolution optoelectronic retinal prosthesis , 2005, Journal of neural engineering.

[2]  Gislin Dagnelie,et al.  Facial recognition using simulated prosthetic pixelized vision. , 2003, Investigative ophthalmology & visual science.

[3]  尚 不二門,et al.  Association for Research in Vision and Ophthalmology (ARVO) に参加して , 2009 .

[4]  K. Turano,et al.  Direction of Gaze while Walking a Simple Route: Persons with Normal Vision and Persons with Retinitis Pigmentosa , 2001, Optometry and vision science : official publication of the American Academy of Optometry.

[5]  Gislin Dagnelie,et al.  Visually guided performance of simple tasks using simulated prosthetic vision. , 2003, Artificial organs.

[6]  T. Duckett,et al.  VOCUS : A Visual Attention System for Object Detection and Goal-directed Search , 2010 .

[7]  K W Horch,et al.  Reading speed with a pixelized vision system. , 1992, Journal of the Optical Society of America. A, Optics and image science.

[8]  N Parikh,et al.  Saliency-based image processing for retinal prostheses , 2010, Journal of neural engineering.

[9]  J. Affeldt,et al.  The feasibility study , 2019, The Information System Consultant’s Handbook.

[10]  Richard A. Normann,et al.  Simulation of a phosphene-based visual field: Visual acuity in a pixelized vision system , 2006, Annals of Biomedical Engineering.

[11]  Alfred Stett,et al.  Subretinal electronic chips allow blind patients to read letters and combine them to words , 2010, Proceedings of the Royal Society B: Biological Sciences.

[12]  C. Veraart,et al.  Position, size and luminosity of phosphenes generated by direct optic nerve stimulation , 2003, Vision Research.

[13]  Jessy D. Dorn,et al.  Preliminary 6 month results from the argustm ii epiretinal prosthesis feasibility study , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[14]  Spencer C. Chen,et al.  Simulating prosthetic vision: II. Measuring functional capacity , 2009, Vision Research.

[15]  Nigel H. Lovell,et al.  Simulated prosthetic visual fixation, saccade, and smooth pursuit , 2005, Vision Research.

[16]  Mark S Humayun,et al.  Frequency and amplitude modulation have different effects on the percepts elicited by retinal stimulation. , 2012, Investigative ophthalmology & visual science.

[17]  Christof Koch,et al.  Feature combination strategies for saliency-based visual attention systems , 2001, J. Electronic Imaging.

[18]  R. Massof,et al.  A self-assessment instrument designed for measuring independent mobility in RP patients: generalizability to glaucoma patients. , 2002, Investigative ophthalmology & visual science.

[19]  C. Koch,et al.  Models of bottom-up and top-down visual attention , 2000 .

[20]  Christof Koch,et al.  A Model of Saliency-Based Visual Attention for Rapid Scene Analysis , 2009 .

[21]  K. Horch,et al.  Mobility performance with a pixelized vision system , 1992, Vision Research.

[22]  Spencer C. Chen,et al.  Simulating prosthetic vision: I. Visual models of phosphenes , 2009, Vision Research.

[23]  C. Koch,et al.  Computational modelling of visual attention , 2001, Nature Reviews Neuroscience.

[24]  Gislin Dagnelie,et al.  Paragraph text reading using a pixelized prosthetic vision simulator: parameter dependence and task learning in free-viewing conditions. , 2006, Investigative ophthalmology & visual science.

[25]  Gislin Dagnelie,et al.  Real and virtual mobility performance in simulated prosthetic vision , 2007, Journal of neural engineering.

[26]  Simone Frintrop,et al.  Goal-Directed Search with a Top-Down Modulated Computational Attention System , 2005, DAGM-Symposium.

[27]  Gislin Dagnelie,et al.  Detection, eye–hand coordination and virtual mobility performance in simulated vision for a cortical visual prosthesis device , 2009, Journal of neural engineering.

[28]  Avi Caspi,et al.  Feasibility study of a retinal prosthesis: spatial vision with a 16-electrode implant. , 2009, Archives of ophthalmology.

[29]  Jessy D. Dorn,et al.  Blind subjects implanted with the Argus II retinal prosthesis are able to improve performance in a spatial-motor task , 2010, British Journal of Ophthalmology.

[30]  J. Weiland,et al.  Visual performance using a retinal prosthesis in three subjects with retinitis pigmentosa. , 2007, American journal of ophthalmology.

[31]  C. Koch,et al.  A saliency-based search mechanism for overt and covert shifts of visual attention , 2000, Vision Research.

[32]  Armand R. Tanguay,et al.  Biomimetic image processing for retinal prostheses: Peripheral saliency cues , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.