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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...
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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:
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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.
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简单的3D姿势功能支持人类和机器社会场景理解

Wenshuo Qin, Leyla Isik

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    科学领域:

    • 认知科学 认知科学
    • 计算机视觉 计算机视觉
    • 人工智能的人工智能

    背景情况:

    • 人类社会互动的识别是毫不费力,但在计算上是复杂的.
    • 目前的深度神经网络 (DNN) 难以识别社交互动.

    研究的目的:

    • 调查人类是否使用3D视觉空间姿势进行社会判断.
    • 为了比较3D的预测能力,将信息与DNN进行比较,以获得社会感知.

    主要方法:

    • 一个新的管道从视频中提取了3D身体关节位置.
    • 用3D身体关节和DNN嵌入来预测人类的社会判断.
    • 功能集被减少到最小的3D和2D姿势信息.

    主要成果:

    • 在预测社会判断方面,3D身体关节的表现优于大多数DNN.
    • 最少的3D姿势特征,而不是2D,对于预测是必要的,也是足够的.
    • 这些3D功能改善了DNN与社会任务的调整和性能.

    结论:

    • 人类的社会感知依赖于明确的3D姿势信息.
    • 3D视觉空间信息对于理解社会互动至关重要.
    • 结合3D姿势可以增强人工社会智能.