Contents Preface vii 1 Introduction 1 1.1 Background................................. 2 1.1.1 Core components and mechanism of action . . . . . . . . . . . . . 2 1.1.2 Phospheneperception........................ 2 1.1.3 Limitations of phosphene vision . . . . . . . . . . . . . . . . . . . 4 1.1.4 The relevance of scene simplification . . . . . . . . . . . . . . . . 4 1.1.5 Deep neural networks for prosthetic vision . . . . . . . . . . . . . 4 1.1.6 Prototyping with simulated prosthetic vision . . . . . . . . . . . . 5 1.2 Optimization through digital simulations . . . . . . . . . . . . . . . . . . 5 1.2.1 Researchaims............................ 5 2 Real-world indoor mobility with simulated prosthetic vision 9 2.1 Introduction ................................ 10 2.2 Materialsandmethods........................... 11 2.2.1 Participants............................. 11 2.2.2 Experimentalsetup ......................... 12 2.2.3 Imageprocessing .......................... 12 2.2.4 Phosphenesimulation........................ 13 2.2.5 Experimentalprocedure. . . . . . . . . . . . . . . . . . . . . . . 14 2.2.6 Randomization ........................... 15 2.2.7 Statisticalanalysis.......................... 15 2.3 Results ................................... 16 2.3.1 Generalresults............................ 16 2.3.2 Phospheneresolution........................ 17 2.3.3 Theeffectofscenecomplexity. . . . . . . . . . . . . . . . . . . . 17 2.3.4 The effect of image processing: SharpNet versus CED . . . . . . . . 18 2.3.5 Userexperience........................... 18 2.4 Discussion ................................. 19 2.4.1 Mobility with simulated cortical prosthetic vision . . . . . . . . . . 19 2.4.2 The effect of visual complexity . . . . . . . . . . . . . . . . . . . . 20 2.4.3 Feasibility of deep learning-based surface-boundary detection for scenesimplification......................... 21 2.4.4 Limitations and future directions . . . . . . . . . . . . . . . . . . 22 2.5 Conclusion................................. 23 3 Towards a task-based computational evaluation benchmark 25 3.1 Introduction ................................ 26 3.1.1 Relatedwork............................. 26 iii
RkJQdWJsaXNoZXIy MTk4NDMw