Perceiving 3D structure in natural images is an immense computational challenge for the visual system. While many previous studies focused on the perception of rigid 3D objects, we applied a novel method on a common set of non-rigid objects—static images of the human body in the natural world. We investigated to what extent human ability to interpret 3D poses in natural images depends on the typicality of the underlying 3D pose and the informativeness of the viewpoint. Using a novel 2AFC pose matching task, we measured how well subjects were able to match a target natural pose image with one of two comparison, synthetic body images from a different viewpoint—one was rendered with the same 3D pose parameters as the target while the other was a distractor rendered with added noises on joint angles. We found that performance for typical poses was measurably better than atypical poses; however, we found no significant difference between informative and less informative viewpoints. Further comparisons of 2D and 3D pose matching models on the same task showed that 3D body knowledge is particularly important when interpreting images of atypical poses. These results suggested that human ability to interpret 3D poses depends on pose typicality but not viewpoint informativeness, and that humans probably use prior knowledge of 3D pose structures.
|Original language||English (US)|
|Number of pages||7|
|State||Published - 2021|
|Event||43rd Annual Meeting of the Cognitive Science Society: Comparative Cognition: Animal Minds, CogSci 2021 - Virtual, Online, Austria|
Duration: Jul 26 2021 → Jul 29 2021
|Conference||43rd Annual Meeting of the Cognitive Science Society: Comparative Cognition: Animal Minds, CogSci 2021|
|Period||7/26/21 → 7/29/21|
Bibliographical noteFunding Information:
We would like to thank Stephen Engel for helpful comments and suggestions on an early draft of this paper. This work was supported by National Institutes of Health with grant NIH R01 EY029700.
© Cognitive Science Society: Comparative Cognition: Animal Minds, CogSci 2021.All rights reserved.
- 3d pose
- human body
- natural images