Overview and Prospects of Visibility Analysis Approaches

This paper conducts a systematic literature review on visibility analysis, aiming to develop a comprehensive classification framework. Visibility analysis is categorized into 2D, 2.5D, and 3D analyses, summarizing its extensive application fields and research dimensions. Chronologically, this paper reviews various algorithms, comparing their advantages and limitations in terms of processing speed, accuracy, and applicability. It highlights current challenges, such as dynamic scene analysis and high-resolution data processing, and proposes optimization strategies like employing data dimensionality reduction, integrating eye-tracking data, and using deep learning to enhance robustness. This review offers a practical classification framework and insights for future research trends in visibility analysis.