Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Vision01:24

Vision

Vision is the result of light being detected and transduced into neural signals by the retina of the eye. This information is then further analyzed and interpreted by the brain. First, light enters the front of the eye and is focused by the cornea and lens onto the retina—a thin sheet of neural tissue lining the back of the eye. Because of refraction through the convex lens of the eye, images are projected onto the retina upside-down and reversed.
Visual System01:26

Visual System

Light enters the eye through the cornea, a transparent, dome-shaped surface covering the surface of the eyeball that helps to direct and focus incoming light. This light is then channeled toward the pupil, an adjustable opening whose size is controlled by the iris. The iris, a pigmented muscle, regulates the amount of light entering the eye by contracting or dilating the pupil, thereby ensuring optimal light levels for clear vision.
Once through the pupil, the light passes through the lens, a...
Gestalt Principles of Perception01:21

Gestalt Principles of Perception

Gestalt principles provide a framework for understanding how humans perceive objects as unified wholes within their context. These principles are essential in explaining the cognitive processes that make sense of complex visual stimuli by organizing them into coherent groups. One fundamental principle is proximity, which posits that objects located close to each other are perceived as a collective group. For instance, when dots are positioned near one another, the visual system interprets them...
Parallel Processing01:20

Parallel Processing

The brain processes sensory information rapidly due to parallel processing, which involves sending data across multiple neural pathways at the same time. This method allows the brain to manage various sensory qualities, such as shapes, colors, movements, and locations, all concurrently. For instance, when observing a forest landscape, the brain simultaneously processes the movement of leaves, the shapes of trees, the depth between them, and the various shades of green. This enables a quick and...
Concepts and Prototypes01:24

Concepts and Prototypes

The human nervous system handles vast amounts of information by translating sensory stimuli into neural impulses, which the brain processes, creating thoughts expressed through language or stored as memories. The brain also synthesizes information from emotions and memories, which significantly influence thoughts and behaviors. This intricate process creates a comprehensive mental picture.
The brain organizes this information using concepts, which are mental categories grouping linguistic data,...
Perception01:28

Perception

Perception is a fundamental psychological process that enables individuals to organize, interpret, and consciously experience sensory information. This process is crucial for understanding and interacting with the world around us. It includes both bottom-up and top-down processing, each playing a distinct role in how we perceive our environment.
Bottom-up processing begins at the sensory level, where receptors detect external environmental stimuli. These could include the tactile sensation of...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

IRF1 is a context-dependent homeostatic gatekeeper of basal immunity and antiviral readiness.

The Journal of biological chemistry·2026
Same author

Neural correlates of minimal recognizable configurations in the human brain.

Cell reports·2025
Same author

Human-like scene interpretation by a guided counterstream processing.

Proceedings of the National Academy of Sciences of the United States of America·2023
Same author

Paradoxical activation of chronic lymphocytic leukemia cells by ruxolitinib <i>in vitro</i> and <i>in vivo</i>.

Frontiers in oncology·2023
Same author

Gelatin Stabilizes Nebulized Proteins in Pulmonary Drug Delivery against COVID-19.

ACS biomaterials science & engineering·2022
Same author

Gaze following requires early visual experience.

Proceedings of the National Academy of Sciences of the United States of America·2022
Same journal

Chemotactic self-organization captures the dynamics of mammalian hair follicle patterning.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same journal

Tomographic imaging of superconducting order using particle-hole interference.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same journal

Inhibitory potential of autologous neutralizing antibodies sets quantitative limits on the rebound-competent HIV-1 reservoir.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same journal

Inferring epidemiological parameters under an infectious phylogeography model with visitor dynamics.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same journal

Analytical modeling for suction cup designs for skin-interfaced wearable devices.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same journal

Improving cell-free metabolism through direct integration of artificial respiratory chains.

Proceedings of the National Academy of Sciences of the United States of America·2026
See all related articles

Related Experiment Video

Updated: May 18, 2026

Visualizing Visual Adaptation
04:43

Visualizing Visual Adaptation

Published on: April 24, 2017

From simple innate biases to complex visual concepts.

Shimon Ullman1, Daniel Harari, Nimrod Dorfman

  • 1Department of Mathematics and Computer Science, Weizmann Institute of Science, Rehovot 76100, Israel. shimon.ullman@weizmann.ac.il

Proceedings of the National Academy of Sciences of the United States of America
|September 27, 2012
PubMed
Summary
This summary is machine-generated.

Infant vision models learn to recognize hands and gaze direction from videos using a novel "mover event" detection mechanism. This innate system guides learning without supervision, mirroring infant development for complex visual recognition.

More Related Videos

Creating Objects and Object Categories for Studying Perception and Perceptual Learning
14:38

Creating Objects and Object Categories for Studying Perception and Perceptual Learning

Published on: November 2, 2012

Automated Charting of the Visual Space of Housefly Compound Eyes
08:34

Automated Charting of the Visual Space of Housefly Compound Eyes

Published on: March 31, 2022

Related Experiment Videos

Last Updated: May 18, 2026

Visualizing Visual Adaptation
04:43

Visualizing Visual Adaptation

Published on: April 24, 2017

Creating Objects and Object Categories for Studying Perception and Perceptual Learning
14:38

Creating Objects and Object Categories for Studying Perception and Perceptual Learning

Published on: November 2, 2012

Automated Charting of the Visual Space of Housefly Compound Eyes
08:34

Automated Charting of the Visual Space of Housefly Compound Eyes

Published on: March 31, 2022

Area of Science:

  • Computational vision
  • Developmental psychology
  • Machine learning

Background:

  • Infants rapidly acquire complex visual recognition skills, such as identifying hands and gaze direction, which remain challenging for current AI.
  • Existing computational models often require extensive labeled data or struggle with the nuances of naturalistic visual input.
  • The gap between infant learning capabilities and AI performance highlights a need for more biologically plausible and efficient learning mechanisms.

Purpose of the Study:

  • To develop a computational model capable of unsupervised learning for recognizing human hands and gaze direction in natural videos.
  • To investigate the role of an innate 'mover event' detection mechanism as an internal teaching signal for guiding visual concept acquisition.
  • To demonstrate how domain-specific 'proto-concepts' can facilitate learning of statistically inconspicuous but significant visual information.

Main Methods:

  • A novel algorithm was developed, processing streams of natural videos without supervision.
  • The model utilizes an empirically motivated innate mechanism: detection of 'mover events' (moving regions causing changes in stationary regions upon contact).
  • This 'mover event' detection serves as an internal teaching signal to guide the learning of hand and gaze representations.

Main Results:

  • The model successfully learned to detect human hands by appearance and context, and to recognize gaze direction in complex natural scenes.
  • 'Mover events' proved to be a more effective internal teaching signal compared to alternative cues for efficient representation acquisition.
  • The system demonstrated the ability to acquire meaningful concepts from statistically inconspicuous sensory input, guided by innate proto-concepts.

Conclusions:

  • An unsupervised learning model guided by 'mover events' can effectively learn challenging visual recognition tasks, mimicking infant learning.
  • Domain-specific innate mechanisms ('proto-concepts') are crucial for bootstrapping learning and acquiring significant visual representations from raw data.
  • This approach offers a pathway for developing more robust and human-like AI systems for visual perception and understanding.