让视觉系统主动感知环境,提升机器人等场景的决策能力。
Active Visual Perception: Opportunities and Challenges
- 系统通过移动传感器或交互来主动获取关键信息
- 在复杂环境中比静态感知更有效,但需实时处理数据
- 适合机器人、自动驾驶等需要动态响应的领域
主动视觉感知指系统通过感知与行动动态参与环境,根据目标或不确定性调整行为。与仅依赖视觉数据的被动系统不同,主动感知系统可引导注意力、移动传感器或与物体交互,以获取更具信息量的数据。该方法在复杂环境中尤为有效,传统静态感知难以提供足够信息。主动视觉感知在机器人、自动驾驶、人机交互和监控系统中具有关键作用。然而,其广泛应用仍面临挑战:复杂视觉数据的实时处理、动态环境中的决策,以及多模态感知输入的融合。本文全面探讨了主动视觉感知的机遇与挑战,梳理了其潜力、当前研究进展及必须克服的障碍。
原文摘要 · Abstract (English)
Active visual perception refers to the ability of a system to dynamically engage with its environment through sensing and action, allowing it to modify its behavior in response to specific goals or uncertainties. Unlike passive systems that rely solely on visual data, active visual perception systems can direct attention, move sensors, or interact with objects to acquire more informative data. This approach is particularly powerful in complex environments where static sensing methods may not provide sufficient information. Active visual perception plays a critical role in numerous applications, including robotics, autonomous vehicles, human-computer interaction, and surveillance systems. However, despite its significant promise, there are several challenges that need to be addressed, including real-time processing of complex visual data, decision-making in dynamic environments, and integrating multimodal sensory inputs. This paper explores both the opportunities and challenges inherent in active visual perception, providing a comprehensive overview of its potential, current research, and the obstacles that must be overcome for broader adoption.
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