Practical and Precise Projector-Camera Calibration

Abstract

Projectors are important display devices for large scale augmented reality applications. However, precisely calibrating projectors with large focus distances implies a trade-off between practicality and accuracy. People either need a huge calibration board or a precise 3D model [12]. In this paper, we present a practical projectorcamera calibration method to solve this problem. The user only needs a small calibration board to calibrate the system regardless of the focus distance of the projector. Results show that the rootmean-squared re-projection error (RMSE) for a 450cm projection distance is only about 4mm, even though it is calibrated using a small B4 (250 × 353mm) calibration board.

Recent Advances in Projection Mapping Algorithms, Hardware and Applications

“…It calibrates the projector via planar surfaces by treating the projector as an inverse of a camera and using structured light patterns to estimate with a single camera where each projector pixel is located on the plane. Recently, this process was simplified by using self-identifying projected blob patterns, which can also be robustly detected when projected onto planes which are placed significantly out of the focus plane of the projector [YNM16]. Related plane-based methods also nicely summarizes further-related methods and differences between them [DRS12].…”

End-To-End Projector Photometric Compensation

“…In theory, the projector compensation process is a very complicated nonlinear function involving the camera and the projector sensor radiometric responses [24], lens distortion/vignetting [20], defocus [35,37], surface material reflectance and inter-reflection [33]. A great amount of effort has been dedicated to designing practical and accurate compensation models, which can be roughly categorized into context-independent [9,11,26,30] and context-aware ones [1,2,24,33].…”

“…Despite largely simplifying the compensation problem, the context-independent assumption is usually violated in practice, due to many factors such as projector distance-tosurface, lens distortion, defocus and surface inter-reflection [33,35,37]. Moreover, it is clear that a projector ray can illuminate multiple surface patches, a patch can be illuminated by the inter-reflection of its surrounding patches, and a camera pixel is also determined by rays reflected by multiple patches.…”

A Single-Shot-Per-Pose Camera-Projector Calibration System for Imperfect Planar Targets

“…Most existing camera-projector pair calibration methods apply Zhang's method [39], where the 3D-2D correspondences between the points on the calibration board and the projector image are computed by some transformations. Regardless of a multi-shot or single-shot method, their transformations fall into one of the following methods: global homography [2, 7-9, 14, 16, 21, 22, 35], local homography [19,20], direct pixel-to-pixel transformation [37] and incremental projector image pre-warp [3,6,28,34,38].…”

“…However, a disadvantage is that it is slow and computationally expensive due to multiple shots, e.g., [20] requires about 20 shots and captures for each pose. Incremental methods [3,6,19,28,34,38] also belong to multi-shot, since the projected pattern is incrementally adjusted to fit the printed pattern until a perfect superimposition is achieved, which requires at least two shots per pose.…”