Dense Ground Truth for Indoor Localization Competitions: Foot-mounted IMU-Enhanced Evaluation
Indoor localization competitions, such as IPIN Track 3, are crucial for benchmarking smartphone-based localization solutions. However, their current evaluation relies on a limited number of sparse, manually placed, and individually georeferenced ground truth (GT) points. This deployment process is c...
| Authors: | , , |
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| Format: | article |
| Status: | Versión aceptada para publicación |
| Publication Date: | 2025 |
| Country: | España |
| Institution: | Consejo Superior de Investigaciones Científicas (CSIC) |
| Repository: | DIGITAL.CSIC. Repositorio Institucional del CSIC |
| OAI Identifier: | oai:digital.csic.es:10261/423088 |
| Online Access: | http://hdl.handle.net/10261/423088 |
| Access Level: | Open access |
| Keyword: | IPIN competition Track 3 Foot-mounted IMU Ground-truth generation |
| Summary: | Indoor localization competitions, such as IPIN Track 3, are crucial for benchmarking smartphone-based localization solutions. However, their current evaluation relies on a limited number of sparse, manually placed, and individually georeferenced ground truth (GT) points. This deployment process is costly and labor-intensive, and the inherent GT sparsity restricts evaluation granularity. It frequently obscures performance nuances and significant position estimation errors that occur between sparse points, consequently limiting comprehensive scoring. This paper proposes a novel method to generate a dense, high-fidelity GT trajectory for competition evaluation without requiring additional manual GT deployment. Our approach fuses a dense, relative trajectory, derived from a footmounted Inertial Measurement Unit (IMU) using Zero-Velocity Updates (ZUPT), with the existing sparse, highly accurate surveyed GT points. This fusion is achieved through a robust segment-wise rigid alignment method, precisely translating and rotating individual trajectory segments, followed by a final global trajectory smoothing. The resulting dense GT enables a more granular and continuous evaluation of competitor trajectories at their native IMU output frequency (e.g., 100 Hz). This offers a more comprehensive and fair assessment, providing enhanced diagnostic capabilities. We outline the methodology, discuss key implementation considerations, and propose an evaluation strategy for the generated GT, highlighting its potential to significantly enhance future indoor localization benchmarks. |
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