Method of learning a parameter to estimate posture of an articulated object and method of estimating posture of an articulated object
First Claim
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1. A learning method, comprising:
- iteratively learning a parameter based on an estimation position and a depth feature corresponding to the estimation position, the parameter being used to estimate a posture of an articulated object in a training image and the estimation position corresponding to an iteration count, whereinthe iteratively learning includes computing the estimation position based on an estimation position corresponding to a previous iteration count, a depth feature corresponding to the previous iteration count, and a parameter corresponding to the previous iteration count.
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Abstract
A method of learning a parameter to estimate a posture of an articulated object, and a method of estimating the posture of the articulated object are provided. A parameter used to estimate a posture of an articulated object may be iteratively learned based on a depth feature corresponding to an iteration count, and the posture of the articulated object may be estimated based on the learned parameter.
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Citations
18 Claims
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1. A learning method, comprising:
iteratively learning a parameter based on an estimation position and a depth feature corresponding to the estimation position, the parameter being used to estimate a posture of an articulated object in a training image and the estimation position corresponding to an iteration count, wherein the iteratively learning includes computing the estimation position based on an estimation position corresponding to a previous iteration count, a depth feature corresponding to the previous iteration count, and a parameter corresponding to the previous iteration count. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. An estimation method, comprising:
iteratively estimating position information of parts of an articulated object included in an input image based on an estimation position corresponding to an iteration count, a depth feature corresponding to the estimation position, and a parameter corresponding to the iteration count, wherein the iteratively estimating includes computing the estimation position based on an estimation position corresponding to a previous iteration count, a depth feature corresponding to the previous iteration count, and a parameter corresponding to the previous iteration count. - View Dependent Claims (12, 13, 14, 15, 16, 17, 18)
Specification