We propose HeadCross, a head-based interaction method to select targets on VR and AR head-mounted displays (HMD). Using HeadCross, users control the pointer with head movements and to select a target, users move the pointer into the target and then back across the target boundary. In this way, users can select targets without using their hands, which is helpful when users' hands are occupied by other tasks, e.g., while holding the handrails. However, a major challenge for head-based methods is the false positive problems: unintentional head movements may be incorrectly recognized as HeadCross gestures and trigger the selections. To address this issue, we first conduct a user study (Study 1) to observe user behavior while performing HeadCross and identify the behavior differences between HeadCross and other types of head movements. Based on the results, we discuss design implications, extract useful features, and develop the recognition algorithm for HeadCross. To evaluate HeadCross, we conduct two user studies. In Study 2, we compared HeadCross to the dwell-based selection method, button-press method, and mid-air gesture-based method. Two typical target selection tasks (text entry and menu selection) are tested on both VR and AR interfaces. Results showed that compared to the dwell-based method, HeadCross improved the sense of control; and compared to two hand-based methods, HeadCross improved the interaction efficiency and reduced fatigue. In Study 3, we compared HeadCross to three alternative designs of head-only selection methods. Results show that HeadCross was perceived to be significantly faster than the alternatives. We conclude with the discussion on the interaction potential and limitations of HeadCross.

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Programming a smart home is an iterative process in which users configure and test the automation during the in-situ experience with IoT space. However, current end-user programming mechanisms are primarily preset configurations on GUI and fail to leverage in-situ behaviors and context. This paper proposed in-situ programming (ISP) as a novel programming paradigm for AIoT automation that extensively leverages users' natural in-situ interaction with the smart environment. We built a Wizard-of-Oz system and conducted a user-enactment study to explore users' behavior models in this paradigm. We identified a dynamic programming flow in which participants iteratively configure and confirm through query, control, edit, and test. We especially identified a novel method "snapshot" for automation configuration and a novel method "simulation" for automation testing, in which participants leverage ambient responses and in-situ interaction. Based on our findings, we proposed design spaces on dynamic programming flow, coherency and clarity of interface, and state and scene management to build an ideal in-situ programming experience.