场景知觉研究综述及展望
A Review and Prospect of Scene Perception Research

场景知觉是指人们如何感知和处理真实环境中的复杂信息。这些场景包括物体和背景两个重要的组成部分，并根据加工水平不同，可以分为三种不同的类型。对于场景信息的处理机制，存在多种理论解释，如直觉整合模型、特征整合模型、贝叶斯层级模型、导向搜索模型、背景引导模型和双通道加工模型。研究者已经尝试采用自上而下和自下而上两种方式来解释场景信息的提取和加工，并尝试从二者交互的角度进行解释。此外，不同的实验目的和技术，如搜索范式、变化觉察范式、物体觉察范式、眼动范式和背景提示范式等，被用于研究场景信息的知觉问题。但是，场景的定义、不同理论模型间以及范式间的整合和不同加工阶段的加工方式仍需要进一步深入和探讨。
Scene perception refers to how people perceive and process complex information in real-world environments. These scenes consist of two important components, objects and backgrounds, and can be categorized into three different types depending on the level of processing. There are multiple theoretical explanations for how scene information is processed, including intuitive integration models, feature integration models, Bayesian hierarchical models, guided search models, background guidance models, and dual-channel processing models. Researchers have attempted to explain the extraction and processing of scene information using both top-down and bottom-up approaches, and have tried to explain the interaction between the two. In addition, different experimental paradigms and techniques, such as search paradigms, change detection paradigms, object perception paradigms, eye movement paradigms, and background cueing paradigms, have been used to study perception problems related to scene information. However, the definition of scenes, the integration of different theoretical models and paradigms, and the processing methods of different stages of processing still need further exploration and discussion.