Leveraging Motion Tracking for Intuitive Interactions in a Tablet-Based 3D Scene Annotation System

In the rapidly evolving field of computer vision, efficient and accurate annotation of 3D scenes plays a crucial role. While automation has streamlined this process, manual intervention is still essential for obtaining precise annotations. Existing annotation tools often lack intuitive interactions and efficient interfaces, particularly when it comes to annotating complex elements such as 3D bounding boxes, 6D human poses, and semantic relationships in a 3D scene. Therefore, it is often time-consuming and error-prone. Emerging technologies such as augmented reality (AR) and virtual reality (VR) have shown potential to provide an immersive and interactive environment for annotators to label objects and their relationships. However, the cost and accessibility of these technologies can be a barrier to their widespread adoption. This work introduces a novel tablet-based system that utilizes built-in motion tracking to facilitate an efficient and intuitive 3D scene annotation process. The system supports a variety of annotation tasks and leverages the tracking and mobility features of the tablet to enhance user interactions. Through a thorough user study investigating three distinct tasks - creating bounding boxes, adjusting human poses, and annotating scene relationships - we evaluate the effectiveness and usability of two interaction methods: touch-based interactions and hybrid interactions that utilize both touch and device motion tracking. Our results suggest that leveraging the tablet's motion tracking feature could lead to more intuitive and efficient annotation processes. This work contributes to the understanding of tablet-based interaction and the potential it holds for annotating complex 3D scenes.