4D Attention: Comprehensive Framework for Spatio-Temporal Gaze Mapping
원문 초록
This study presents a framework for capturing human attention in the spatio-temporal domain using eye-tracking glasses. Attention mapping is a key technology for human perceptual activity analysis or Human-Robot Interaction (HRI) to support human visual cognition; however, measuring human attention in dynamic environments is challenging owing to the difficulty in localizing the subject and dealing with moving objects. To address this, we present a comprehensive framework, 4D Attention, for unified gaze mapping onto static and dynamic objects. Specifically, we estimate the glasses pose by leveraging a loose coupling of direct visual localization and Inertial Measurement Unit (IMU) values. Further, by installing reconstruction components into our framework, dynamic objects not captured in the 3D environment map are instantiated based on the input images. Finally, a scene rendering component synthesizes a first-person view with identification (ID) textures and performs direct 2D-3D gaze association. Quantitative evaluations showed the effectiveness of our framework. Additionally, we demonstrated the applications of 4D Attention through experiments in real situations.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
OracleFusion: Assisting the Decipherment of Oracle Bone Script with Structurally Constrained Semantic Typography
Why Not Replace? Sustaining Long-Term Visual Localization via Handcrafted-Learned Feature Collaboration on CPU
To Glue or Not to Glue? Classical vs Learned Image Matching for Mobile Mapping Cameras to Textured Semantic 3D Building Models
LiftFeat: 3D Geometry-Aware Local Feature Matching
Visual Re-Ranking with Non-Visual Side Information
Re-thinking Temporal Search for Long-Form Video Understanding
토론
이 논문과 연결된 포럼 글이 아직 없습니다.