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相关概念视频

Depth Perception and Spatial Vision01:15

Depth Perception and Spatial Vision

1.8K
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.
1.8K
Gestalt Principles of Perception01:21

Gestalt Principles of Perception

1.1K
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...
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Computed Tomography01:10

Computed Tomography

8.0K
Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...
8.0K
Perceptual Constancy01:12

Perceptual Constancy

1.3K
Perceptual constancy is the ability to recognize that objects remain consistent and unchanged even when their appearance varies due to changes in sensory input. There are four main types of perceptual constancy: size constancy, shape constancy, color constancy, and brightness constancy.
Size constancy is the recognition that an object remains the same size, even when its image on the retina changes. For instance, a bus is perceived to be large enough to carry people, even if it looks tiny from...
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Reducing Line Loss01:18

Reducing Line Loss

366
In a three-phase circuit, line loss is an indicator of energy dissipated as heat due to the resistance of transmission lines. To address this, incorporating transformers into the system—a step-up transformer at the source and a step-down transformer at the load—is a strategic solution. Two three-phase transformers are introduced to improve this.
With a step-up transformer at the source, the voltage is increased, thereby reducing the current in the transmission lines since power loss in...
366
Curvilinear Motion: Rectangular Components01:23

Curvilinear Motion: Rectangular Components

1.1K
Curvilinear motion characterizes the movement of a particle or object along a curved path, notably evident when envisioning a car navigating a winding road. If the car starts at point A, its position vector is established within a fixed frame of reference, where the ratio of the position vector to its magnitude signifies the unit vector pointing in the position vector's direction.
As the car advances, its position evolves over time. Quantifying the car's velocity involves computing the...
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相关实验视频

Updated: Jan 17, 2026

Photorealistic Learned Landscapes for Augmented Reality
06:54

Photorealistic Learned Landscapes for Augmented Reality

Published on: June 27, 2025

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结构意识的生成点云压缩用于视觉感知.

Yichen Zhou, Xinfeng Zhang, Yingzhan Xu

    IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
    |September 16, 2025
    PubMed
    概括
    此摘要是机器生成的。

    这项研究引入了压缩3D点云数据的新框架,提高了人类感知的视觉质量. 该方法提高了3D模型的编码效率和重建精度.

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    Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique
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    Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

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    相关实验视频

    Last Updated: Jan 17, 2026

    Photorealistic Learned Landscapes for Augmented Reality
    06:54

    Photorealistic Learned Landscapes for Augmented Reality

    Published on: June 27, 2025

    685
    Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique
    04:48

    Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

    Published on: July 5, 2024

    736

    科学领域:

    • 计算机视觉 计算机视觉
    • 3D数据处理 3D数据处理
    • 信号压缩 压缩信号

    背景情况:

    • 点云数据对于沉浸式体验等3D应用至关重要.
    • 在保持感知质量的同时,对大型,高精度点云进行有效的压缩是一个重大挑战.

    研究的目的:

    • 开发一个新的结构意识的生成点云压缩框架.
    • 为了提高人类视觉的压缩效率和感知质量.

    主要方法:

    • 编码器捕获全球和本地规模的结构意识信息,对人类视觉敏感.
    • 解码器使用由编码器信息指导的渐进式生成重建.
    • 一个基于概率云的区分器评估点存在概率分布.

    主要成果:

    • 该框架有效地从多个尺度上捕捉了结构的重要性.
    • 概率云区分器可以提高发电机的准确性.
    • 高精度点云是通过修剪低概率点来生成的.

    结论:

    • 拟议的框架提供了卓越的编码效率和感知质量.
    • 它在生成高质量的点云方面表现出有效性.
    • 这种方法解决了视觉应用程序点云压缩的关键挑战.