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Related Concept Videos

Tactile and Chemical Senses01:27

Tactile and Chemical Senses

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Tactile senses encompass touch, temperature, and pain, each mediated by specific receptors. Touch receptors detect mechanical energy or pressure against the skin. Sensory fibers from these receptors enter the spinal cord and relay information to the brain stem. Here, most fibers cross over to the opposite side of the brain. The touch information then moves to the thalamus, which projects a map of the body's surface onto the somatosensory areas of the parietal lobes in the cerebral cortex.
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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.
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Design Example: Resistive Touchscreen01:14

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Depth Perception and Spatial Vision01:15

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Depth perception is the ability to perceive objects three-dimensionally. It relies on two types of cues: binocular and monocular. Binocular cues depend on the combination of images from both eyes and how the eyes work together. Since the eyes are in slightly different positions, each eye captures a slightly different image. This disparity between images, known as binocular disparity, helps the brain interpret depth. When the brain compares these images, it determines the distance to an object.
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Related Experiment Video

Updated: Mar 2, 2026

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment
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Object recognition combining vision and touch.

Tadeo Corradi1, Peter Hall1, Pejman Iravani1

  • 1Department of Mechanical Engineering, University of Bath, Claverton Down, Bath, BA27AY UK.

Robotics and Biomimetics
|May 9, 2017
PubMed
Summary
This summary is machine-generated.

Combining vision and touch improves object recognition, especially with limited tactile data or impaired vision. The "posterior product" method offers the highest accuracy, demonstrating the power of multi-modal learning in robotics.

Keywords:
Object recognitionRobotic visionSensor fusionTactile sensors

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Area of Science:

  • Robotics
  • Computer Vision
  • Machine Learning
  • Sensory Fusion

Background:

  • Object recognition is crucial for robotics, but often relies on single sensory modalities.
  • Limited tactile training data and impaired vision pose significant challenges for current recognition systems.
  • Human multi-sensory integration offers a model for robust object recognition.

Purpose of the Study:

  • To explore methods for combining vision and touch for enhanced object recognition.
  • To investigate the performance of multi-modal systems with limited tactile data and impaired vision.
  • To compare different fusion techniques for integrating visual and tactile information.

Main Methods:

  • Extended a tactile recognition model by integrating a vision system.
  • Implemented three fusion methods: vector concatenation, posterior averaging, and posterior product.
  • Evaluated recognition accuracy and learning speed (number of training samples required).

Main Results:

  • The 'posterior product' fusion method achieved the highest recognition accuracy.
  • Multi-modal recognition surpassed single-modality recognition when all data was pooled.
  • Multi-modal systems demonstrated faster learning, requiring fewer samples under visual impairment.

Conclusions:

  • Multi-modal sensory fusion, particularly using the 'posterior product' method, significantly enhances object recognition accuracy.
  • Integrating vision and touch provides robustness, especially in scenarios with limited data or sensor degradation.
  • Robotic systems benefit from multi-modal approaches for improved performance and efficiency in object recognition tasks.