Active Visual Perception: Opportunities and Challenges

TL;DR

This paper reviews the potential and challenges of active visual perception systems that dynamically interact with environments to improve data acquisition, highlighting their importance in robotics, autonomous vehicles, and surveillance.

Contribution

It provides a comprehensive overview of active visual perception, discussing its opportunities, current research, and the key challenges to wider implementation.

Findings

Active visual perception enhances data collection in complex environments.

Real-time processing and decision-making are major challenges.

Integration of multimodal sensory inputs is crucial for system effectiveness.

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.