Development of object recognition

Abstract

Object recognition is a fundamental cognitive ability that helps humans organize the visual world into meaningful perceptual units. To understand the nature of object recognition in humans fully, it is important to understand its developmental origins in infancy and the processes by which it reaches maturity. At birth, infants demonstrate a wide range of visual competencies including the ability to discriminate and categorize simple shapes. By 6-months, infants readily form holistic and three-dimensional shape representations which allow them to recognize objects in a viewpoint-invariant manner and categorize objects after exposure to only a few exemplars. Remarkably, infants acquire these skills with experience with just a few objects and, on average, only three faces. Several infant-specific biological and experiential constraints support the rapid development of object recognition. For instance, infants are born with innate perceptual biases for features like top-heaviness and symmetry that provide a scaffold for learning objects. Moreover, rather than being a hindrance, low visual acuity in infancy supports the development of holistic shape representations, allowing even newborns to perceptually group elements into a complete shape. Finally, infants visual experience with objects is seemingly ‘self-curated’ to support object learning, such that they display a bias for viewpoints that maximally display objects’ shape structure. Indeed, incorporating infant-like constraints into artificial neural network models improves the model’s performance on object recognition tasks. The neural mechanisms that support these abilities in infancy, however, may be different than adults. Although early visual cortex is relatively mature in infants, category-selective regions in higher-level areas of the ventral visual pathway do not mature fully until at least adolescence. Instead, neuroimaging and computational modelling research suggests that object recognition in infancy is supported by a more distributed neural code that represents lower-level features. Altogether, these studies suggest that the development of object recognition is bootstrapped by biological and experiential factors specific to infants’ developmental niche. By understanding the origins and development of object recognition, we gain a deeper understanding of the mechanisms that support object recognition in adulthood.

Human EEG and artificial neural networks reveal disentangled representations of object real-world size in natural images

“…Increasingly, research has begun to use ANNs to study the mechanisms of object recognition (Ayzenberg et al, 2023;Cichy & Kaiser, 2019;Doerig et al, 2023;Kanwisher et al, 2023). We can explore how the human brain processes information at different levels by comparing brain activity with models (Cichy et al, 2016;S.…”

The developmental trajectory of object recognition robustness: Children are like small adults but unlike big deep neural networks

“…What about our impressive object recognition abilities, particularly robustness to image degradations? Behavioral research investigating the development of object recognition (robustness) in children (after 2 years of age) and adolescents is comparatively sparse, however (for an overview, see the recent preprint by ( Ayzenberg & Behrmann, 2022 ). A number of reviews have pointed out the lack of such studies ( Rentschler, Jüttner, Osman, Müller, & Caelli, 2004 ; Nishimura, Scherf, & Behrmann, 2009 ; Smith, 2009 ).…”