Abstract
Non-contact human body measurement plays an important role in surveillance, physical healthcare, on-line business and virtual fitting. Current methods for measuring the human body without physical contact usually cannot handle humans wearing clothes, which limits their applicability in public environments. In this paper, we propose an effective solution that can measure accurate parameters of the human body with large-scale motion from a Kinect sensor, assuming that the people are wearing clothes. Because motion can drive clothes attached to the human body loosely or tightly, we adopt a space-time analysis to mine the information across the posture variations. Using this information, we recover the human body, regardless of the effect of clothes, and measure the human body parameters accurately. Experimental results show that our system can perform more accurate parameter estimation on the human body than state-of-the-art methods.
Highlights
Non-contact human body measurement plays an important role in surveillance, physical healthcare, on-line business and virtual fitting
Cui et al [7] estimated a model of good quality from 12 views of depth maps and RGB images, but their solution suffers from large-scale motion
For building the correspondence between the RGB key points and depth points, we project the depth map to the RGB image, and we find the nearest depth points to be the correspondence of the RGB points
Summary
Non-contact human body measurement plays an important role in surveillance, physical healthcare, on-line business and virtual fitting. Laser range scanners can provide human body reconstruction, which can be used for Sensors 2013, 13 accurate biometric measurements. Laser range scanners cannot be an everyday choice for human body measurement in the short term. Marker-less multi-view systems [1,2,3,4] have become more and more proficient at acquiring human body models because of the efforts of researchers; these solutions always take too much space and are difficult to set up. Weiss et al [6] obtained four different views of depth maps and RGBimages from the Kinect sensor, and estimated a consistent model from them. Cui et al [7] estimated a model of good quality from 12 views of depth maps and RGB images, but their solution suffers from large-scale motion. Human body measurement with large-scale motion is still an open problem
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