Ray-Sector Targeting: An Efficient Disambiguation Selection Technique Based on Target Feature in Virtual Reality

Object selection is a fundamental interaction method in virtual reality, but selecting occluded objects poses great challenges for users.Current techniques mostly adopt progressive approaches or add extra components to the pointing ray, yet they have two major drawbacks: losing original context and performing suboptimally in rapid target localization and selection accuracy. This paper proposes an efficient disambiguation selection technique called Ray-Sector Targeting (RST). The RST features a visual indicator called “Sector Target” (SeTar) that helps users acquire information about the target. We design a corresponding selection and error correction mechanism centered around SeTar to enhance the speed and accuracy of user selections when dealing with occluded targets. To evaluate the performance of RST, we conduct a user study by comparing it with two sophisticated techniques in virtual dense environments. The experimental result demonstrates that RST achieves significantly superior performance in both selection efficiency and accuracy.