A method for printing on an item, that includes generating a scanned shape of the item, performing a lookup of the scanned shape in a shape database, making a determination that the scanned shape matches a saved shape in the shape database, and based on the determination, measuring an item rotation of the item, generating a transformed print image based on the item rotation, causing a printhead to print on the item using the transformed print image.

A method for printing on an item, that includes generating a scanned shape of the item, performing a lookup of the scanned shape in a shape database, making a determination that the scanned shape matches a saved shape in the shape database, and based on the determination, measuring an item rotation of the item, generating a transformed print image based on the item rotation, causing a printhead to print on the item using the transformed print image.

Embodiments are disclosed for computing accurate smooth occluding contours. In one embodiment, a method of computing accurate smooth occluding contours includes projecting a boundary polygon associated with a first region of a three-dimensional (3D) object to a two-dimensional (2D) image plane, the boundary polygon comprising a plurality of contour vertices and edges connecting the plurality of contour vertices, triangulating the first region in the 2D image plane to generate a 2D triangulation, and generating a 3D mesh for the first region by mapping the 2D triangulation to the 3D object.

Embodiments are disclosed for computing accurate smooth occluding contours. In one embodiment, a method of computing accurate smooth occluding contours includes projecting a boundary polygon associated with a first region of a three-dimensional (3D) object to a two-dimensional (2D) image plane, the boundary polygon comprising a plurality of contour vertices and edges connecting the plurality of contour vertices, triangulating the first region in the 2D image plane to generate a 2D triangulation, and generating a 3D mesh for the first region by mapping the 2D triangulation to the 3D object.

Various implementations disclosed herein include devices, systems, and methods that create additional depth frames where a depth camera runs at a lower frame rate than a light intensity camera. Rather than upconverting the depth frames by simply repeating a previous depth camera frame, additional depth frames are created by adjusting some of the depth values of a prior frame based on the RGB camera data (e.g., by “dragging” depths from their positions in the prior depth frame to new positions for a new frame). Specifically, a contour image is generated, and changes in the contour image are used to determine how to adjust (e.g., drag) the depth values for the additional depth frames. The contour image may be based on a mask (e.g., occlusions masks identifying where the hand occludes the virtual cube).

Various implementations disclosed herein include devices, systems, and methods that create additional depth frames where a depth camera runs at a lower frame rate than a light intensity camera. Rather than upconverting the depth frames by simply repeating a previous depth camera frame, additional depth frames are created by adjusting some of the depth values of a prior frame based on the RGB camera data (e.g., by “dragging” depths from their positions in the prior depth frame to new positions for a new frame). Specifically, a contour image is generated, and changes in the contour image are used to determine how to adjust (e.g., drag) the depth values for the additional depth frames. The contour image may be based on a mask (e.g., occlusions masks identifying where the hand occludes the virtual cube).

The present invention provides an automatic container loading and unloading apparatus and method. The apparatus comprises: a data acquisition module, used for scanning a container truck panel to obtain laser point cloud data; a data preprocessing module, used for segmenting a laser point cloud on a surface of the container truck panel from the laser point cloud data; a key point extraction module, used for performing edge extraction on the laser point cloud on the surface of the container truck panel to obtain discrete points on edges of the keel of the container truck panel; and a straight line fitting module, used for performing random sample consensus straight line fitting on the discrete points on the edges of the keel of the container truck panel to obtain spatial straight lines of the edges of the keel of the truck panel. The automatic container loading and unloading apparatus and method provided by the present invention using spatial straight lines on the edges of the keel of the container truck panel for computing processing, thereby achieving stronger robustness and higher accuracy, so that a container is loaded onto the container truck panel with higher precision and lower calculation amount.

A determining method includes acquiring first direction information, when a first captured image captured by an imaging device is acquired, by referring to a storage storing a plurality of pieces of direction information indicating a plurality of directions associating with respective shapes of a plurality of contours of an object according to a plurality of directions of the object, the first direction information associated with a shape of a contour that corresponds to a shape of a contour of the subject included in the acquired first captured image among the shapes of the contours, and acquiring second direction information, when a second captured image newly captured by the imaging device is acquired, by referring to the storage to acquire second direction information associated with a shape of a contour that corresponds to a contour of the subject included in acquired second captured image among the shapes of contours.

A determining method includes acquiring first direction information, when a first captured image captured by an imaging device is acquired, by referring to a storage storing a plurality of pieces of direction information indicating a plurality of directions associating with respective shapes of a plurality of contours of an object according to a plurality of directions of the object, the first direction information associated with a shape of a contour that corresponds to a shape of a contour of the subject included in the acquired first captured image among the shapes of the contours, and acquiring second direction information, when a second captured image newly captured by the imaging device is acquired, by referring to the storage to acquire second direction information associated with a shape of a contour that corresponds to a contour of the subject included in acquired second captured image among the shapes of contours.

A method for image processing includes: receiving a third two-dimensional image and a depth image corresponding to the third two-dimensional image, wherein the third two-dimensional image and the depth image include a face; establishing a three-dimensional model of the face according to the depth image; rotating the three-dimensional model of the face by a first angle; projecting the three-dimensional model of the face rotated by the first angle to an image coordinate system of the third two-dimensional image; and building a three-dimensional model of a background region of the third two-dimensional image, processing a background region of an image projected to the image coordinate system of the third two-dimensional image to obtain a fourth image.