CVOct 9, 2018

Visual Localization of Key Positions for Visually Impaired People

arXiv:1810.03790v112 citations
Originality Incremental advance
AI Analysis

This addresses the critical need for more precise navigational assistance for visually impaired individuals, though it appears incremental as it builds on existing visual localization methods.

The paper tackled the problem of inaccurate localization for visually impaired people at key outdoor positions like gates and bus stations by proposing a visual localization algorithm that uses multiple image descriptors and prior GNSS signals, achieving improved positioning precision in practical wearable system tests.

On the off-the-shelf navigational assistance devices, the localization precision is limited to the signal error of global navigation satellite system (GNSS). During travelling outdoors, the inaccurately localization perplexes visually impaired people, especially at key positions, such as gates, bus stations or intersections. The visual localization is a feasible approach to improving the positioning precision of assistive devices. Using multiple image descriptors, the paper proposes a robust and efficient visual localization algorithm, which takes advantage of priori GNSS signals and multi-modal images to achieve the accurate localization of key positions. In the experiments, we implement the approach on the wearable system and test the performance of visual localization under practical scenarios.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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