Action-specific perception, or perception-action, is a psychological theory that people perceive their environment and events within it in terms of their ability to act. This theory hence suggests that a person's capability to carry out a particular task affects how they perceive the different aspects and methods involved in that task. For example, softball players who are hitting better see the ball as bigger. Tennis players see the ball as moving slower when they successfully return the ball. In the field of human-computer interaction, alterations in accuracy impact both the perception of size and time, while adjustments in movement speed impact the perception of distance. Furthermore, the perceiver's intention to act is also critical; while the perceiver's ability to perform the intended action influences perception, the perceiver's abilities for unintended actions have little or no effect on perception. Finally, the objective difficulty of the task appears to modulate size, distance, and time perception. Action-specific effects have been documented in a variety of contexts and with a variety of manipulations. The original work was done on perceived slant of hills and perceived distance to targets. Hills look steeper and targets look farther away when wearing a heavy backpack. In addition to walking, many other actions influence perception such as throwing, jumping, falling, reaching, grasping, kicking, hitting, blocking, and swimming. In addition to perceived slant and perceived distance, other aspects of perception are influenced by ability such as size, shape, height, and speed. These results have been documented in athletes such as softball players, golfers, tennis players, swimmers, and people skilled in parkour. However, a criticism would be that these action-specific effects on perception may surface only in extreme cases (e.g., professional athletes) or condition (e.g., steep hills). Recent evidence from virtual reality, indicated that these action-specific effects are observed in both "normal" conditions and average individuals.

À propos de ce résultat
Cette page est générée automatiquement et peut contenir des informations qui ne sont pas correctes, complètes, à jour ou pertinentes par rapport à votre recherche. Il en va de même pour toutes les autres pages de ce site. Veillez à vérifier les informations auprès des sources officielles de l'EPFL.

Graph Chatbot

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.