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The uniform distribution based segmentation technique utilized for accurate detection of multiple humans in a given scenario.
As an application, we present a robot that uses our system of perceptual memory and proximity spaces to 'attend to' multiple humans in a complex and unstructured indoor environment.
In literature, several techniques are implemented for human detection which includes segmentation techniques, feature extraction techniques, classification-based detections, etc. Segmentation techniques for human detection include template matching [12], foreground detection [2], and background subtraction [13], but these methods failed with multiple humans in a scene.
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The purpose of this study was to evaluate the potential biologic effects of oxidized regenerated cellulose, which has been shown in multiple human in vivo studies to reduce postoperative adhesion development, on the messenger RNA levels of transforming growth factor-β1, type I collagen, type III collagen, and fibronectin.
In the first step, multiple humans are detected in the given video sequences by fusion novel uniform and EM segmentation.
Such an example of tracking multiple human targets in a crowded scene is shown in Fig. 8.
Mitochondrial genome is responsible for multiple human diseases in a maternal inherited pattern, yet phenotypes of patients in a same pedigree frequently vary largely.
Fig. 8 Illustration of tracking multiple human targets in a crowded scene [21].
Fig. 6 Illustration of tracking multiple human targets in an outdoor scene.
However, the problem of multiple human tracking in a real complex environment has been less well addressed (e.g. [25]).
Ultra-wideband (UWB) radar with strong anti-jamming performance and high-range resolution can be used to separate multiple human targets in a complex environment.
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