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

Modeling and Similitude01:12

Modeling and Similitude

683
Scaled modeling is a fundamental technique in engineering, enabling the study of large and complex systems by creating smaller, manageable replicas that recreate critical characteristics of the original. In hydrology and civil infrastructure, for example, scaled models of dams help analyze water flow, turbulence, and pressure. This method allows for accurate predictions of real-world behavior within a controlled environment, significantly reducing the cost and time involved in full-scale...
683
Support Reactions in Three Dimensions01:27

Support Reactions in Three Dimensions

1.7K
Support reactions in three dimensions help maintain the stability and equilibrium of various structures and systems. These reactions prevent the system from translating and rotating, ensuring the design can withstand external forces and perform its intended function efficiently and safely. Some of the supports providing support reactions in three dimensions are discussed below:
Ball and Socket Joint is one of the supports allowing free rotation about any axis. This freedom of rotation is...
1.7K
Automatic Processing and Automatic Social Behavior01:28

Automatic Processing and Automatic Social Behavior

284
Automatic processing refers to the cognitive operations that occur without conscious intent or awareness, playing a fundamental role in shaping social cognition and behavior. These processes enable individuals to navigate complex social environments efficiently by relying on mental shortcuts and pre-existing knowledge structures known as schemas. One of the most influential mechanisms underlying automatic processing is priming, which subtly activates mental representations through exposure to...
284
Three-Dimensional Force System:Problem Solving01:30

Three-Dimensional Force System:Problem Solving

1.4K
A three-dimensional force system refers to a scenario in which three forces act simultaneously in three different directions. This type of problem is commonly encountered in physics and engineering, where it is necessary to calculate the resultant force on the system, which can then be used to predict or analyze the behavior of the object or structure under consideration.
To solve a three-dimensional force system, first resolve each force into its respective scalar components. Do this using...
1.4K
Structural Classification of Joints01:20

Structural Classification of Joints

7.8K
Joints, also known as articulations, are classified based on their structural characteristics, i.e., based on whether the articulating surfaces of the adjacent bones are directly connected by fibrous connective tissue or cartilage, or whether the articulating surfaces contact each other within a fluid-filled joint cavity. These differences serve to divide the joints of the body into three structural classifications.
A fibrous joint is where the adjacent bones are united by fibrous connective...
7.8K
Muscles for Facial Expressions01:14

Muscles for Facial Expressions

5.2K
The craniofacial muscles are a collection of approximately 20 thin skeletal muscles situated beneath the skin of the face and scalp. These muscles, primarily responsible for the vast array of human facial expressions, originate from the bones or fibrous structures of the skull and extend outwards to connect with the skin. While most skeletal muscles in the body are enveloped in thick fascia, facial muscles generally have a more delicate fascial covering, with the buccinator muscle being a...
5.2K

You might also read

Related Articles

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

Sort by
Same author

Dissociating spatial frequency reliance from adversarial robustness advantages in neurally guided deep convolutional neural networks.

ArXiv·2026
Same author

Bottom-up and generative computations uniquely explain neural responses across the social brain.

bioRxiv : the preprint server for biology·2026
Same author

Aligning Video Models with Human Social Judgments via Behavior-Guided Fine-Tuning.

ArXiv·2025
Same author

Generative adversarial collaborations: a new model of scientific discourse.

Trends in cognitive sciences·2024
Same author

Early Neural Development of Social Interaction Perception: Evidence from Voxel-Wise Encoding in Young Children and Adults.

The Journal of neuroscience : the official journal of the Society for Neuroscience·2024
Same author

Neural Encoding of Bodies for Primate Social Perception.

The Journal of neuroscience : the official journal of the Society for Neuroscience·2024

Related Experiment Video

Updated: Feb 28, 2026

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

5.5K

Simple 3D Pose Features Support Human and Machine Social Scene Understanding.

Wenshuo Qin1, Leyla Isik1

  • 1Johns Hopkins University.

Arxiv
|February 27, 2026
PubMed
Summary
This summary is machine-generated.

Humans use 3D pose information for social perception, outperforming deep neural networks (DNNs). Minimal 3D features are key for recognizing social interactions and improving DNN performance.

More Related Videos

Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping
09:41

Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping

Published on: April 21, 2023

2.3K
A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis
05:41

A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis

Published on: February 6, 2020

9.9K

Related Experiment Videos

Last Updated: Feb 28, 2026

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

5.5K
Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping
09:41

Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping

Published on: April 21, 2023

2.3K
A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis
05:41

A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis

Published on: February 6, 2020

9.9K

Area of Science:

  • Cognitive Science
  • Computer Vision
  • Artificial Intelligence

Background:

  • Human social interaction recognition is effortless but computationally complex.
  • Current deep neural networks (DNNs) struggle with social interaction recognition.

Purpose of the Study:

  • To investigate if humans use 3D visuospatial pose for social judgments.
  • To compare the predictive power of 3D pose information against DNNs for social perception.

Main Methods:

  • A novel pipeline extracted 3D body joint positions from videos.
  • 3D body joints and DNN embeddings were used to predict human social judgments.
  • Feature sets were reduced to minimal 3D and 2D pose information.

Main Results:

  • 3D body joints outperformed most DNNs in predicting social judgments.
  • Minimal 3D pose features, not 2D, were necessary and sufficient for prediction.
  • These 3D features improved DNN alignment with and performance on social tasks.

Conclusions:

  • Human social perception relies on explicit 3D pose information.
  • 3D visuospatial information is crucial for understanding social interactions.
  • Incorporating 3D pose can enhance artificial social intelligence.