CPC G06T 7/13 (2017.01) [G06T 7/12 (2017.01); G06T 7/90 (2017.01); G06T 9/20 (2013.01); G06V 10/56 (2022.01); G06V 20/647 (2022.01); G06T 2200/04 (2013.01); G06T 2207/10012 (2013.01); G06T 2207/10024 (2013.01); G06T 2207/20021 (2013.01); G06T 2207/20081 (2013.01)] | 18 Claims |
1. A method for three-dimensional edge detection, the method comprising: obtaining, for each of plural two-dimensional slices of a three-dimensional image, a two-dimensional object detection result and a two-dimensional edge detection result; stacking the two-dimensional object detection results into a three-dimensional object detection result, and stacking the two-dimensional edge detection results into a three-dimensional edge detection result E;
performing more than one encoding operation according to a feature map F of the three-dimensional image, the three-dimensional object detection result, and the three-dimensional edge detection result, to obtain an encoding result by
performing a first dot product operation ⊗ on the feature map of the three-dimensional image and the three-dimensional object detection result which is F⊗E, adding a result of the first dot product operation to the three-dimensional edge detection result, and performing a current encoding operation of the result of the first dot product operation added with the three-dimensional edge detection result; and
performing a second dot product operation on an output of the current encoding operation and the three-dimensional object detection result, adding a result of the second dot product operation to the three-dimensional edge detection result, and performing a next encoding operation of the second dot product operation added with the three-dimensional edge detection result, the more than one encoding operation that includes the current encoding operation and the next encoding operation being performed until a last encoding operation of the more than one encoding operation; and
performing, by processing circuitry of a computer device, decoding according to the encoding result, the three-dimensional object detection result, and the three-dimensional edge detection result, to obtain an optimized three-dimensional edge detection result of the three-dimensional image.
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