US 2021/0241476 A1 · TRAINING A POSE DETECTION ALGORITHM, AND DERIVING AN OBJECT POSE USING A TRAINED POSE DETECTION ALGORITHM

Abstract

Training a pose detection algorithm and deriving an object pose using a trained pose detection algorithm. Specifying a first view of a 3D model with respect to a virtual camera, generating a depth map by projecting the 3D model based on the first view, generating a second view by perturbing the first view, selecting reference 2D locations in an overlapping area of the 3D model between the first view and the second view. Transforming the reference 2D locations into a 3D point set corresponding to the second view. For each reference 2D location, calculating a depth difference between the first view and the second view at the reference 2D location. Associating the perturbation between the second view and the first view with the calculated depth differences, and training an algorithm model to identify a pose of an object corresponding to the 3D model.

Claims19

Dependent claims

A non-transitory computer readable medium that embodies instructions that cause one or more processors to perform a method for training an object detection algorithm, the method comprising:

(a) specifying a first view of a 3D model with respect to a virtual camera;
(b) generating a depth map by projecting the 3D model based on the first view;
(c) generating a second view around the first view by perturbing the first view;
(d) selecting reference 2D locations from the first depth map, the reference 2D locations being in an overlapping area of the 3D model between the first view and the second view;
(e) transforming the reference 2D locations into a 3D-point set corresponding to the second view;
(f) for each reference 2D location, calculating a depth difference between the first view and the second view at the reference 2D location using (i) the 3D-point set and (ii) the depth map;
(g) associating the perturbation between the second view and the first view with the calculated depth differences;
and
(h) training an algorithm model using, as an input to the algorithm, the perturbation and the depth difference associated with each other, to identify a pose of an object corresponding to the 3D model.

6 more elements

A non-transitory computer readable medium that embodies instructions that cause one or more processors to perform a method for deriving a pose of an object, the method comprising:

(a) generating a depth map based on sensor data acquired by a depth sensor sensing an object;
(b) deriving a first pose of the object corresponding to the depth map;
(c) acquiring 3D feature points based on a 3D model corresponding to the object;
(d) acquiring 2D feature points by projecting the 3D feature points onto a virtual plane using the first pose;
(e) acquiring depth values from the depth math, the depth values associated with 2D locations of the depth map, the locations being at the same locations as the 2D feature points on the virtual plane;
and
(f) deriving a second pose of the object by applying a trained algorithm model using, as an input to the trained algorithm, a difference between (i) Z coordinate values of the 3D feature points and (ii) the respective depth values.

4 more elements

Dependencies are inferred from the claim text.

Training a pose detection algorithm, and deriving an object pose using a trained pose detection algorithm

Life of this patent

Training a pose detection algorithm, and deriving an object pose using a trained pose detection algorithm

Life of this patent

Abstract

Claims19