Visible Light Positioning With Lamé Curve LEDs: A Generic Approach for Camera Pose Estimation
Wenxuan Pan, Yang Yang, Dong Wei, Zhiyu Zhu, Jintao Wang, Huan Wu, Yao Nie
TL;DR
This work tackles indoor camera pose estimation with limited LEDs and heterogeneous LED shapes by introducing Lamé curves as a unified LED model. It develops LC-VLP, a generic VLP framework featuring an offline LED parameter database, a correspondence-free FreePnP initialization, and a back-projection-based nonlinear refinement that minimizes algebraic distances to Lamé curves. The approach yields substantial accuracy gains over state-of-the-art methods in both circular and rectangular LED scenarios, with simulation results showing over 40% reductions in position error and over 25% in rotation error, and experiments achieving average position errors below 4 cm in heterogeneous settings. By unifying LED geometry into a single parametric form, LC-VLP enables robust, full 6-DoF camera pose estimation in mixed LED environments, supporting practical deployment in real-world indoor positioning systems.
Abstract
Camera-based visible light positioning (VLP) is a promising technique for accurate and low-cost indoor camera pose estimation (CPE). To reduce the number of required light-emitting diodes (LEDs), advanced methods commonly exploit LED shape features for positioning. Although interesting, they are typically restricted to a single LED geometry, leading to failure in heterogeneous LED-shape scenarios. To address this challenge, this paper investigates Lamé curves as a unified representation of common LED shapes and proposes a generic VLP algorithm using Lamé curve-shaped LEDs, termed LC-VLP. In the considered system, multiple ceiling-mounted Lamé curve-shaped LEDs periodically broadcast their curve parameters via visible light communication, which are captured by a camera-equipped receiver. Based on the received LED images and curve parameters, the receiver can estimate the camera pose using LC-VLP. Specifically, an LED database is constructed offline to store the curve parameters, while online positioning is formulated as a nonlinear least-squares problem and solved iteratively. To provide a reliable initialization, a correspondence-free perspective-\textit{n}-points (FreeP\textit{n}P) algorithm is further developed, enabling approximate CPE without any pre-calibrated reference points. The performance of LC-VLP is verified by both simulations and experiments. Simulations show that LC-VLP outperforms state-of-the-art methods in both circular- and rectangular-LED scenarios, achieving reductions of over 40% in position error and 25% in rotation error. Experiments further show that LC-VLP can achieve an average position accuracy of less than 4 cm.