Show, don't tell -- Providing Visual Error Feedback for Handwritten Documents

TL;DR

This paper investigates the challenges of providing visual error feedback for handwritten documents, comparing system approaches and highlighting the need for future research to improve quality.

Contribution

It offers an empirical comparison of modular and end-to-end systems for visual feedback in handwriting and identifies key challenges for advancing this area.

Findings

Both system approaches currently lack acceptable quality

Major challenges in translating handwritten images to feedback are identified

Future research directions are outlined

Abstract

Handwriting remains an essential skill, particularly in education. Therefore, providing visual feedback on handwritten documents is an important but understudied area. We outline the many challenges when going from an image of handwritten input to correctly placed informative error feedback. We empirically compare modular and end-to-end systems and find that both approaches currently do not achieve acceptable overall quality. We identify the major challenges and outline an agenda for future research.