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Studying human behavior from infancy: On the acquisition of infant postural data

机译:从婴儿期研究人类行为:关于婴儿姿势数据的获取

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The study of human behavior using infants as target subjects is very attractive since these individuals are minimally affected by cultural background and display the fastest rates of evolving cognition and physique, opening possibilities to longitudinal but relatively short-term research. Naturally, important customers of infant movement data are healthcare practitioners and scientists at the cutting edge of the understanding of human development and related disorders, in particular Autism Spectrum Disorder (ASD). Here we provide evidence that, as opposed to the current practice, these studies demand non-invasive instrumentation to measure movement, so the right paradigm to obtain the data will most likely depend on computer vision based pose estimation. By surveying the interdisciplinary literature on infant motion capture, we show that, up to now, very little has been done to consider infant data in vision, and no method has treated the problem of measuring infant movement as special problem of its own, but rather a special case of the general human movement capture problem. We oppose this position and propose the use of canonical postures as an implementation of the principle of stability noted by developmental psychologists, and exemplify how these postures and age-related data could be used to potentially improve existing pose estimation systems. We also show preliminary results suggesting that canonical postures may be recognized using global, low-level contour features augmented by mid-level features like elongatedeness; these results are consistent with previous work in infant pose estimation using pressure-based sensors.
机译:使用婴儿作为目标对象的人类行为研究非常有吸引力,因为这些人受文化背景的影响最小,并且显示出最快的认知和体质发展速度,为纵向但相对短期的研究提供了可能性。自然,婴儿运动数据的重要客户是医疗保健从业人员和科学家,他们是了解人类发展和相关疾病(尤其是自闭症谱系障碍(ASD))的前沿。在这里,我们提供的证据表明,与当前的实践相反,这些研究需要使用非侵入性仪器来测量运动,因此获取数据的正确范例极有可能取决于基于计算机视觉的姿势估计。通过调查有关婴儿运动捕获的跨学科文献,我们表明,到目前为止,在视觉方面考虑婴儿数据的工作还很少,并且没有任何方法将测量婴儿运动的问题视为其自身的特殊问题。一般人类运动捕捉问题的特例。我们反对这一立场,并建议使用规范姿势作为发展心理学家指出的稳定原理的实现,并举例说明如何使用这些姿势和与年龄相关的数据来潜在地改善现有的姿势估计系统。我们还显示了初步结果,表明可以使用整体的低级轮廓特征(由中度特征(如拉长度)增强)来识别规范姿势;这些结果与以前使用基于压力的传感器进行婴儿姿势估计的工作一致。

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