Enhancing Saliency Prediction in Monitoring Tasks: The Role of Visual Highlights
원문 초록
This study examines the role of visual highlights in guiding user attention in drone monitoring tasks, employing a simulated interface for observation. The experiment results show that such highlights can significantly expedite the visual attention on the corresponding area. Based on this observation, we leverage both the temporal and spatial information in the highlight to develop a new saliency model: the highlight-informed saliency model (HISM), to infer the visual attention change in the highlight condition. Our findings show the effectiveness of visual highlights in enhancing user attention and demonstrate the potential of incorporating these cues into saliency prediction models.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
CASE: Contrastive Activation for Saliency Estimation
CSPENet: Contour-Aware and Saliency Priors Embedding Network for Infrared Small Target Detection
Uncertainty Guided Refinement for Fine-Grained Salient Object Detection
Mesh Mamba: A Unified State Space Model for Saliency Prediction in Non-Textured and Textured Meshes
A Deep Learning Framework for Visual Attention Prediction and Analysis of News Interfaces
Textured Mesh Saliency: Bridging Geometry and Texture for Human Perception in 3D Graphics
토론
이 논문과 연결된 포럼 글이 아직 없습니다.