Abstract
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.
Abstract (translated)
本研究探讨了在无人机监测任务中，视觉突显在引导用户注意力和识别目标中的作用。为进行观察，我们采用模拟界面进行实验。实验结果表明，这样的突显可以显著加快相应区域的视觉注意力的进程。根据这个观察结果，我们利用突显中的时间和空间信息来开发了一个新的显著性模型：突显通知显著性模型（HISM），以推断突显条件下的视觉注意力变化。我们的研究结果表明视觉突显在增强用户注意力和将这些线索纳入显著性预测模型方面具有有效性。
URL
https://arxiv.org/abs/2405.09695
