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Methods for posing problems in this framework along with advantages of the formulation are discussed.
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The literature proposes several methods for pose variability problems.
The study presents a segmented, least squares method for pose measurement systems, calculates the error correction coefficient, and revises the resulting function of both the relative distance and the angle.
However, acoustic-based methods are effective for posed expressions in staged scenarios but degrades in natural human interaction with spontaneous expression [25].
Further developments in such direction, coupled with increasing computing power, might alleviate the need to rely on faster and less accurate methods such as docking for pose prediction.
To evaluate the accuracy and the precision of the method for 3D pose estimation, presented in the previous section, a set of trials was carefully designed.
Huang et al. [16] propose Gabor feature based multi-class random forest method for head pose estimation.
In this paper we proposed to use a Binary Pattern Run Length matrix based on the random forests method for head pose estimation.
Table 3 Indicative ESC confusion matrix Annotation Left Neutral Right Detection Left 317 320 0 Neutral 15 679 375 Right 0 0 226 Indicative confusion matrix of the ESC method for face pose over the yaw angle on the BU database.
In this study an in vitro assessment is performed of a method for 3D pose estimation of a vertebra with respect to a fluoroscopic imaging system, based upon the comparison between Digital Video Fluoroscopy (DVF) images and DRRs.
This paper has described an automatic method for 3D pose estimation of a vertebra by means of CT and digital video-fluoroscopy and an in vitro assessment using a calibration object was performed.
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