Over the years, gaze input modality has been an easy and demanding human–computer interaction (HCI) method for various applications. The research of gaze-based interactive applications has advanced considerably, as HCIs are no longer constrained to traditional input devices. In this paper, we propose a novel immersive eye-gaze-guided camera (called GazeGuide) that can seamlessly control the movements of a camera mounted on an unmanned aerial vehicle (UAV) from the eye-gaze of a remote user. The video stream captured by the camera is fed into a head-mounted display (HMD) with a binocular eye tracker. The user’s eye-gaze is the sole input modality to maneuver the camera. A user study was conducted considering the static and moving targets of interest in a three-dimensional (3D) space to evaluate the proposed framework. GazeGuide was compared with a state-of-the-art input modality remote controller. The qualitative and quantitative results showed that the proposed GazeGuide performed significantly better than the remote controller.

Acquisition of 3D point cloud data (PCD) using a laser scanner and aligning it with a video frame is a new approach that is efficient for retrofitting comprehensive objects in heavy pipeline industrial facilities. This work contributes a generic framework for interactive retrofitting in a virtual environment and an unmanned aerial vehicle (UAV)-based sensory setup design to acquire PCD. The framework adopts a 4-in-1 alignment using a point cloud registration algorithm for a pre-processed PCD alignment with the partial PCD, and frame-by-frame registration method for video alignment. This work also proposes a virtual interactive retrofitting framework that uses pre-defined 3D computer-aided design models (CAD) with a customized graphical user interface (GUI) and visualization of a 4-in-1 aligned video scene from a UAV camera in a desktop environment. Trials were carried out using the proposed framework in a real environment at a water treatment facility. A qualitative and quantitative study was conducted to evaluate the performance of the proposed generic framework from participants by adopting the appropriate questionnaire and retrofitting task-oriented experiment. Overall, it was found that the proposed framework could be a solution for interactive 3D CAD model retrofitting on a combination of UAV sensory setup-acquired PCD and real-time video from the camera in heavy industrial facilities.

This study proposed a gaze-controlled method for visualization, navigation, and retrofitting of large point cloud data (PCD), produced by unmanned aerial vehicles (UAV) mounted with laser range-scanners. For this purpose, the estimated human gaze point was used to interact with a head-mounted display (HMD) to visualize the PCD and the computer-aided design (CAD) models. Virtual water treat plant pipeline models were considered for retrofitting against the PCD of the actual pipelines. In such an application, the objective was to use the gaze data to interact with the HMD so the virtual retrofitting process was performed by navigating with the eye gaze. It was inferred that the integration of eye gaze tracking for visualization and interaction with the HMD could improve both speed and functionality for human–computer interaction. A usability study was conducted to investigate the speed of the proposed method against the mouse interaction-based retrofitting. In addition, immersion, interface quality and accuracy was analyzed by adopting the appropriate questionnaire and user learning was tested by conducting experiments in iterations from participants. Finally, it was verified whether any negative psychological factors, such as cybersickness, general discomfort, fatigue, headache, eye strain and difficulty concentrating through the survey experiment.