Active Visual Perception: Opportunities and Challenges

TL;DR

Problem: static visual sensing often fails in dynamic, unstructured environments. Approach: a comprehensive survey of opportunities, applications, challenges, and future directions for active visual perception in human-machine systems. Contributions: synthesis of domain-specific opportunities (robotics, HCI, surveillance, environmental monitoring), analysis of core challenges (real-time decision-making, sensor fusion, computational load, safety), and proposed directions including ML advances, sensor tech, collaboration, and ethics. Impact: provides a framework for advancing robust, efficient, and responsible active perception in intelligent automation and human-centered interfaces.

Abstract

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.

Figures (4)

• Figure 1: (a) In retail environments, robots equipped with active visual perception systems dynamically reposition themselves to detect suspicious behaviors. (b) In autonomous vehicles, the system dynamically adjusts its perception modules and viewpoints to detect obstacles. (c) A robot equipped with an active visual perception system participates in a tennis match, adjusting its posture and vision in real time to respond effectively to human actions. (d) In wartime emergency rescue, drones equipped with active visual perception systems can monitor and analyze the environment in real time and quickly locate trapped people.
• Figure 2: Opportunities of active visual perception.
• Figure 3: Challenges of active visual perception.
• Figure 4: Overview of future directions in active visual perception.