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

60.3K
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.
60.3K
Color Vision01:24

Color Vision

1.5K
Color perception begins in the retina, the light-sensitive layer at the back of the eye. Two main theories explain how colors are seen: the trichromatic theory and the opponent-process theory. The trichromatic theory, proposed by Thomas Young in 1802 and extended by Hermann von Helmholtz in 1852, suggests that color vision is based on three types of cone receptors in the retina. These cones are sensitive to different but overlapping ranges of wavelengths corresponding to red, blue, and green.
1.5K
Machines01:19

Machines

581
Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. One example of a machine is the cutting plier, which is used to cut wires by applying forces to its handles. When equal and opposite forces are exerted on the handles of the cutting plier, they cause the cutting edges to come together and apply equal and opposite reaction forces on the wire, which are greater than the applied forces.
A free-body diagram of the...
581
Machines: Problem Solving II01:30

Machines: Problem Solving II

678
Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. Consider a lifting tong carrying a 100 kg load. It comprises movable sections DAF and CBG linked together with member AB.
678
Machines: Problem Solving I01:22

Machines: Problem Solving I

727
A toggle clamp is a mechanical device commonly used for holding and clamping objects in various applications, such as woodworking, metalworking, and assembly operations. Consider a toggle clamp subjected to a force of 200 N at the handle. The vertical clamping force can be calculated, provided the dimensions of the toggle clamp are known.
The toggle clamp system is a machine structure consisting of movable, pin-connected multi-force members that form a stabilized system to transmit forces. The...
727
Integration of Synaptic Events01:28

Integration of Synaptic Events

4.2K
Synaptic integration mainly includes the summation of graded potentials. Graded potentials, regardless of their type, cause subtle alterations in membrane voltage, resulting in either depolarization or hyperpolarization. These incremental changes, when combined or summed, can propel the neuron toward its threshold. Consider, for example, a membrane experiencing a +15 mV shift, causing it to depolarize from -70 mV to -55 mV. In this scenario, graded potentials govern the membrane's ability to...
4.2K

You might also read

Related Articles

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

Sort by
Same author

Polarization-State-Dependent Charge Screening in Metal-Ferroelectric-Metal Memcapacitors Enabled by an IGZO Oxygen Reservoir Layer.

ACS applied materials & interfaces·2026
Same author

FPGA-based reconfigurable scanning and data acquisition system for scanning electron microscopy.

Applied microscopy·2026
Same author

Enhancing Oxygen Evolution Reaction and Stability in Proton-Conducting Solid Oxide Electrolysis Cells (p-SOECs) via a Porous Gadolinium-Doped Ceria Interlayer.

ACS applied materials & interfaces·2026
Same author

All-Oxide ITO/HZO/WO<sub><i>x</i></sub> Ferroelectric Tunnel Junctions with Oxygen-Engineered Interfaces for Highly Endurable Neuromorphic Computing.

ACS applied materials & interfaces·2026
Same author

Ascertaining the Transient State Pivotal for Fast Carrier Migration in Halide Perovskites.

Journal of the American Chemical Society·2026
Same author

Asymmetric Polarization in FE/AFE Bilayer HZO Memcapacitors via Composition-Induced Built-in Bias.

ACS applied materials & interfaces·2026

Related Experiment Video

Updated: Feb 14, 2026

Author Spotlight: A Machine-Vision Approach to Transmission Electron Microscopy Workflows, Results Analysis and Data Management
10:23

Author Spotlight: A Machine-Vision Approach to Transmission Electron Microscopy Workflows, Results Analysis and Data Management

Published on: June 23, 2023

3.6K

Event-Based Machine Vision for Edge AI Computing.

Paul K J Park1,2, Junseok Kim1, Juhyun Ko1

  • 1Samsung Electronics, Hwaseong 18448, Republic of Korea.

Sensors (Basel, Switzerland)
|February 13, 2026
PubMed
Summary
This summary is machine-generated.

Event-based sensors and efficient AI algorithms enable real-time smart-home perception. This approach significantly reduces data and computation for human detection, pose estimation, and hand gesture recognition on edge devices.

Keywords:
dynamic vision sensoredge AIevent-based visionhand posture recognitionhome occupancy sensinghuman detectionhuman pose estimationneuromorphicpolarity-agnostic event representationtimestamp-based encoding

More Related Videos

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation
08:47

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation

Published on: February 9, 2024

2.1K
Constructing and Visualizing Models using Mime-based Machine-learning Framework
06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

2.6K

Related Experiment Videos

Last Updated: Feb 14, 2026

Author Spotlight: A Machine-Vision Approach to Transmission Electron Microscopy Workflows, Results Analysis and Data Management
10:23

Author Spotlight: A Machine-Vision Approach to Transmission Electron Microscopy Workflows, Results Analysis and Data Management

Published on: June 23, 2023

3.6K
Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation
08:47

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation

Published on: February 9, 2024

2.1K
Constructing and Visualizing Models using Mime-based Machine-learning Framework
06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

2.6K

Area of Science:

  • Computer Vision
  • Artificial Intelligence of Things (AIoT)
  • Edge Computing

Background:

  • Event-based sensors, like Dynamic Vision Sensors (DVS), offer sparse, motion-centric data ideal for low-bandwidth, always-on perception.
  • Resource-constrained edge devices require efficient algorithms for real-time AI tasks.

Purpose of the Study:

  • To develop an event-based machine vision framework for smart-home AIoT applications.
  • To enable efficient human/object detection, 2D human pose estimation, and hand posture recognition using event data.

Main Methods:

  • Developed timestamp-based, polarity-agnostic recency encoding to preserve motion structure and reduce background noise.
  • Optimized task-specific neural networks through architectural reduction and mixed-bit quantization for sparse event images.
  • Evaluated performance on human detection, pose estimation, and hand posture recognition tasks.

Main Results:

  • Raw DVS data stream size reduced by ~30x compared to conventional CMOS video.
  • Human detection computation reduced by over 11x (5.8 G to 81 M FLOPs) with a runtime speed-up from 172 ms to 15 ms.
  • Pose estimation model size reduced from 127 MB to 19 MB, with inference time decreasing from 70 ms to 6 ms, maintaining high accuracy.
  • Hand posture recognition achieved 99.19% recall with 14.31 ms latency.

Conclusions:

  • Event-based sensing combined with lightweight inference is a practical solution for privacy-friendly, real-time perception on edge devices.
  • The proposed framework demonstrates significant improvements in data efficiency and computational performance for smart-home AIoT.