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Related Concept Videos

Stereoisomers02:32

Stereoisomers

On the basis of mirror symmetry, stereoisomers of an organic molecule can be further classified into diastereomers and enantiomers. Diastereomers are stereoisomers that are not mirror images of each other. Substituted alkenes, such as the cis and trans isomers of 2-butene, are diastereomers, as these molecules exhibit different spatial orientations of their constituent atoms, are not mirror images of each other, and do not interconvert. Here, the interconversion is suppressed due to restricted...
Electronic Distance Measuring Instruments01:30

Electronic Distance Measuring Instruments

Electronic Distance Measuring Instruments (EDMs) are essential tools in modern surveying, offering precise distance measurements by emitting electromagnetic signals and calculating the time required for these signals to travel to a target and return. Two primary types of signals are used in EDMs — light waves and microwaves — each suited to specific environmental and distance requirements. Light-wave-based EDMs utilize either infrared or laser light, providing high accuracy over short distances...
Stereoisomerism02:52

Stereoisomerism

Isomerism in Complexes
Isomers are different chemical species that have the same chemical formula.
Transition metal complexes often exist as geometric isomers, in which the same atoms are connected through the same types of bonds but with differences in their orientation in space. Coordination complexes with two different ligands in the cis and trans positions from a ligand of interest form isomers. For example, the octahedral [Co(NH3)4Cl2]+ ion has two isomers (Figure 1) In the cis...
Linear Approximation in Frequency Domain01:26

Linear Approximation in Frequency Domain

Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
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Distance Problem01:29

Distance Problem

When an object's velocity changes over time, the total distance traveled can be determined by summing small displacement intervals over short increments. This approach approximates the true distance through numerical summation and the use of integral calculus. An estimate of the total displacement can be obtained by measuring velocity at regular intervals and multiplying each value by the corresponding time step.If a runner accelerates over the first three seconds of a race, speed measurements...
Echo01:06

Echo

The human ear cannot distinguish between two sources of sound if they happen to reach within a specific time interval, typically 0.1 seconds apart. More than this, and they are perceived as separate sources.
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Robotized Testing of Camera Positions to Determine Ideal Configuration for Stereo 3D Visualization of Open-Heart Surgery
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Robotized Testing of Camera Positions to Determine Ideal Configuration for Stereo 3D Visualization of Open-Heart Surgery

Published on: August 12, 2021

Stereo matching using epipolar distance transform.

Qingxiong Yang1, Narendra Ahuja

  • 1Department of Computer Science, City University of Hong Kong, Hong Kong. liiton.research@gmail.com

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|July 18, 2012
PubMed
Summary
This summary is machine-generated.

We introduce the epipolar distance transform to improve stereo matching in low-texture image regions. This affine-invariant transform enhances pixel distinguishability and boosts reconstruction accuracy with existing algorithms.

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Area of Science:

  • Computer Vision
  • Image Processing
  • Geometric Computer Vision

Background:

  • Matching low-texture regions is a significant challenge in computer vision.
  • Existing stereo matching algorithms struggle with areas lacking distinct features.

Purpose of the Study:

  • To propose a novel image transform for effective matching in low-texture regions.
  • To enhance the accuracy and robustness of stereo matching algorithms.

Main Methods:

  • Developed the epipolar distance transform, converting image intensities to relative locations along epipolar lines.
  • Theoretically proved the affine invariance of the transform.
  • Applied the transform to existing stereo matching algorithms.

Main Results:

  • The epipolar distance transform effectively distinguishes pixels in low-texture regions.
  • Demonstrated improved stereo matching accuracy on real indoor and outdoor images.
  • Showcased robustness in highly textured scenes and for keypoint detection/description.

Conclusions:

  • The epipolar distance transform is a simple, effective, and computationally efficient solution for low-texture stereo matching.
  • The transform is compatible with existing stereo algorithms, enhancing their performance.
  • Achieved real-time processing speeds (9 fps) on standard hardware.