生物运动信息加工模型  

The Models of Biological Motion Perception

作　　者：陈婷婷[1] 丁锦红[1] 蒋长好[2] 

机构地区：[1]首都师范大学心理系"学习与认知"重点实验室,北京100048 [2]首都体育学院运动机能评定和技术分析实验室,北京100191

出　　处：《心理科学》2012年第6期1524-1529,共6页Journal of Psychological Science

基　　金：国家自然科学基金项目(30970891);教育部高校博士点基金项目(20091108110001);教育部人文社科项目(11YJA190008);北京市科技面上项目(SQKM201210029003);北京市教育科学规划重点项目(AGA09096)的资助

摘　　要：人类可以从生物体的各种运动行为中获得丰富的社会信息,以满足社会交往的需求。视觉系统对生物运动信息的加工是一个复杂的过程,不同于对其他普通客体的加工能力。研究者们采用不同的方法,分别从各自的角度来研究这一过程,同时也建立了一系列模型。其中早期模型关注视觉系统加工生物运动信息的过程和方法;近期模型则采用脑成像手段构建生物运动信息加工的神经网络。这些模型包含了很多有价值的研究成果,但是也存在需要进一步完善的地方。The perception of biological motion is crucial to the survival of human beings. Examining the models of biological motion perception is helpful to understanding the complex process. Previous models emphasize how the visual system encodes biological motion. The kinetic-geometric model for visual vector analysis that originally developed in the study of perception of motion combinations of the mechanical type was applied to these biological motion patterns. For the ＂ planarity assumption＂ in the interpretation of biological motion, the specific problem addressed is how the three-dimensional structure and motions of animal limbs may be computed from the twodimensional motions of their projected images. Most recent studies take into account the neural mechanism of biological motion perception. The hierarchical neural model by Giese and Poggio uses a neurophysiologically plausible and quantitative model as a tool for organizing and making sense of the experimental data, despite their growing size and complexity. The template-matching model from configural form cues is addressed by Lange and Lappe. They presented a computational model based on neurally plausible assumptions to elucidate the contributions of motion and form signals to biological motion perception and the computations in the underlying brain network. The model simulates receptive fields for images of the static human body, as found by neuroimaging studies, and temporally integrates their responses by leaky integrator neurons. The model reveals a high correlation to data obtained by neurophysiological, neuroimaging, and psychophysical studies. These above-mentioned models were proposed to explain key experimental results and to plan new experiments related to the recognition of biological movements. The paper also points to issues that cannot be addressed by these models and by the available experimental results.

关 键 词：生物运动 光点运动序列 早期模型 近期模型 

分 类 号：B841[哲学宗教—基础心理学]