This paper presents a systematic evaluation of five controller-free pointing techniques for 2D target selection in AR, using ISO 9241-411. We compared them across multiple depths (2 m, 6 m, 10 m) in terms of movement time, accuracy, throughput, and workload (NASA TLX). Head- and eye-based pointing significantly outperformed the hand-based methods (Finger, Wrist, and Arm); Head input was the most accurate and remained the most consistent across depth. Depth significantly impacted performance, with complex interactions with target size and distance. Our results offer a comprehensive empirical basis for selecting appropriate controller-free techniques in depth-varying AR tasks.

翻译：本文基于ISO 9241-411标准，对五种面向增强现实二维目标选择任务的无控制器指向技术进行了系统性评估。我们从运动时间、准确率、吞吐量和任务负荷（NASA TLX）四个维度，对比了这些技术在多个深度层级（2米、6米、10米）下的表现。基于头部和眼部的指向技术显著优于基于手部的指向技术（手指、手腕、手臂）；其中头部输入在准确率方面表现最优，且在不同深度下保持最佳稳定性。深度对性能具有显著影响，并与目标尺寸和距离存在复杂的交互作用。本研究结果为在深度变化的增强现实任务中选择合适的无控制器指向技术提供了全面的实证依据。