Abstract: Methods and systems for determining rotation and clipping parameters for images of unit load devices (ULDs) are disclosed herein. An example method includes capturing a set of image data featuring a ULD. The example method may further include locating a fiducial marker proximate to the ULD within the set of image data. The example method may further include cropping the set of image data, based upon the located fiducial marker, to generate a set of marker point data and a set of floor point data. The example method may further include rotating the set of image data based upon the set of marker point data and the set of floor point data, and clipping the rotated set of image data based upon the set of marker point data and the set of floor point data.

Abstract: Methods and systems for determining rotation and clipping parameters for images of unit load devices (ULDs) are disclosed herein. An example method includes capturing a set of image data featuring a ULD. The example method may further include locating a fiducial marker proximate to the ULD within the set of image data. The example method may further include cropping the set of image data, based upon the located fiducial marker, to generate a set of marker point data and a set of floor point data. The example method may further include rotating the set of image data based upon the set of marker point data and the set of floor point data, and clipping the rotated set of image data based upon the set of marker point data and the set of floor point data.

Abstract: A mount system for a monitoring device is disclosed. The mount system may include an extension arm attached to a device structure for housing the monitoring device. The mount system may include an alignment cup coupled to a support structure, wherein the extension arm is received through a through hole in a base of the alignment cup, and an oblong fitting attached to the extension arm opposite the device structure, wherein the oblong fitting is complementarily shaped to be received within the alignment cup to be received within the alignment cup, such that when the oblong fitting is received within the alignment cup, the device structure is aligned into a monitoring location. The mount system may include a dampening component between the support structure and the extension arm to bias the device structure into the monitoring location.

Abstract: A device and system for image capture and mapping of a trailer are provided. The device and system facilitate image capture of an interior of the trailer by a monitor. The device comprises a reflective surface configured to reflect light between the trailer interior and monitor to modify a field of view (FOV) of the monitor and a label affixed to the reflective surface. The label comprises a non-reflecting indicia indicative of a position of the label in the trailer interior and the monitor has a FOV comprising the reflective surface and label. The system comprises a monitor configured to capture at least one image of the trailer interior, the reflective surface, and at least one label comprising an indicia indicative of a position of the at least one label in the trailer interior. The monitor has a FOV comprising at least one of the reflective surface and the at least one label.

Abstract: A method includes: obtaining, from a sensor disposed on a transporter, a set of beacon identifiers and proximity indicators, the beacon identifiers emitted by respective beacons mounted proximate to a boundary separating an exterior of a container from an interior of the container; determining whether the set of beacon identifiers and proximity indicators indicates a transition of the transporter across the boundary; when the determination is affirmative, detecting, based on the set of beacon identifiers and proximity indicators, a direction of travel of the transporter relative to the boundary; and generating a transition event including an identifier of the transporter, an identifier of the container, and the direction of travel.

Abstract: Three-dimensional (3D) depth imaging systems and methods are disclosed for assessing an orientation with respect to a container. A 3D-depth camera captures 3D image data of a shipping container. A container feature assessment application determines a representative container point cloud and (a) converts the 3D image data into 2D depth image data; (b) compares the 2D depth image data to one or more template image data; (c) performs segmentation to extract 3D point cloud features; (d) determines exterior features of the shipping container and assesses the exterior features using an exterior features metric; (e) determines interior features of the shipping container and assesses the interior features using an interior features metric; and (f) generates an orientation adjustment instruction for indicating to an operator to orient the 3D-depth camera in a second direction for use during a shipping container loading session, wherein the second direction is different than the first direction.

Abstract: A mount system for a monitoring device is disclosed. The mount system may include an extension arm attached to a device structure for housing the monitoring device. The mount system may include an alignment cup coupled to a support structure, wherein the extension arm is received through a through hole in a base of the alignment cup, and an oblong fitting attached to the extension arm opposite the device structure, wherein the oblong fitting is complementarily shaped to be received within the alignment cup to be received within the alignment cup, such that when the oblong fitting is received within the alignment cup, the device structure is aligned into a monitoring location. The mount system may include a dampening component between the support structure and the extension arm to bias the device structure into the monitoring location.

Abstract: Methods and systems for determining rotation and clipping parameters for images of unit load devices (ULDs) are disclosed herein. An example method includes capturing a set of image data featuring a ULD. The example method may further include locating a fiducial marker proximate to the ULD within the set of image data. The example method may further include cropping the set of image data, based upon the located fiducial marker, to generate a set of marker point data and a set of floor point data. The example method may further include rotating the set of image data based upon the set of marker point data and the set of floor point data, and clipping the rotated set of image data based upon the set of marker point data and the set of floor point data.

Abstract: A mount system for a monitoring device is disclosed. The mount system may include an extension arm attached to a device structure for housing the monitoring device. The mount system may include an alignment cup coupled to a support structure, wherein the extension arm is received through a through hole in a base of the alignment cup, and an oblong fitting attached to the extension arm opposite the device structure, wherein the oblong fitting is complementarily shaped to be received within the alignment cup to be received within the alignment cup, such that when the oblong fitting is received within the alignment cup, the device structure is aligned into a monitoring location. The mount system may include a dampening component between the support structure and the extension arm to bias the device structure into the monitoring location.

Abstract: A mount system for a monitoring device is disclosed. The mount system may include an extension arm attached to a device structure for housing the monitoring device. The mount system may include an alignment cup coupled to a support structure, wherein the extension arm is received through a through hole in a base of the alignment cup, and an oblong fitting attached to the extension arm opposite the device structure, wherein the oblong fitting is complementarily shaped to be received within the alignment cup to be received within the alignment cup, such that when the oblong fitting is received within the alignment cup, the device structure is aligned into a monitoring location. The mount system may include a dampening component between the support structure and the extension arm to bias the device structure into the monitoring location.

Abstract: Three-dimensional (3D) depth imaging systems and methods are disclosed for assessing an orientation with respect to a container. A 3D-depth camera captures 3D image data of a shipping container. A container feature assessment application determines a representative container point cloud and (a) converts the 3D image data into 2D depth image data; (b) compares the 2D depth image data to one or more template image data; (c) performs segmentation to extract 3D point cloud features; (d) determines exterior features of the shipping container and assesses the exterior features using an exterior features metric; (e) determines interior features of the shipping container and assesses the interior features using an interior features metric; and (f) generates an orientation adjustment instruction for indicating to an operator to orient the 3D-depth camera in a second direction for use during a shipping container loading session, wherein the second direction is different than the first direction.

Abstract: Three-dimensional (3D) depth imaging systems and methods are disclosed for assessing an orientation with respect to a container. A 3D-depth camera captures 3D image data of a shipping container. A container feature assessment application determines a representative container point cloud and (a) converts the 3D image data into 2D depth image data; (b) compares the 2D depth image data to one or more template image data; (c) performs segmentation to extract 3D point cloud features; (d) determines exterior features of the shipping container and assesses the exterior features using an exterior features metric; (e) determines interior features of the shipping container and assesses the interior features using an interior features metric; and (f) generates an orientation adjustment instruction for indicating to an operator to orient the 3D-depth camera in a second direction for use during a shipping container loading session, wherein the second direction is different than the first direction.

Abstract: A method of determining a location for placement of a package in an imaging controller includes: obtaining depth data of a package space; detecting an occluded portion of the depth data representing an area of the package space obstructed by an occlusion; retrieving stored unobstructed depth data representing the area of the package space in the absence of the occlusion; replacing the occluded portion with the unobstructed depth data to generate patched depth data; obtaining, based on the patched depth data, a location within the package space for placement of a package; and presenting an indication of the location.

Abstract: Methods, systems, and apparatus for segmenting and dimensioning objects are disclosed. An example method disclosed herein includes determining a first sensor of a plurality of sensors toward which a vehicle is moving based on image data generating by the plurality of sensors; designating the first sensor as a reference sensor; combining the image data from the plurality of sensors to generate combined image data representative of the vehicle and an object carried by the vehicle, the combining based on reference sensor; generating a plurality of clusters based on the combined image data; and identifying a first one of the clusters nearest the reference sensor as the object.

Abstract: A method and apparatus for receiving a depth frame from a depth sensor oriented towards an open end of a shipping container, the depth frame comprising a plurality of grid elements that each have a respective depth value, identifying one or more occlusions in the depth frame, correcting the one or more occlusions in the depth frame using one or more temporally proximate depth frames, and outputting the corrected depth frame for fullness estimation.

Abstract: Three-dimensional (3D) depth imaging systems and methods are disclosed for assessing an orientation with respect to a container. A 3D-depth camera captures 3D image data of a shipping container. A container feature assessment application determines a representative container point cloud and (a) converts the 3D image data into 2D depth image data; (b) compares the 2D depth image data to one or more template image data; (c) performs segmentation to extract 3D point cloud features; (d) determines exterior features of the shipping container and assesses the exterior features using an exterior features metric; (e) determines interior features of the shipping container and assesses the interior features using an interior features metric; and (f) generates an orientation adjustment instruction for indicating to an operator to orient the 3D-depth camera in a second direction for use during a shipping container loading session, wherein the second direction is different than the first direction.

Abstract: A method of determining a location for placement of a package in an imaging controller includes: obtaining depth data of a package space; detecting an occluded portion of the depth data representing an area of the package space obstructed by an occlusion; retrieving stored unobstructed depth data representing the area of the package space in the absence of the occlusion; replacing the occluded portion with the unobstructed depth data to generate patched depth data; obtaining, based on the patched depth data, a location within the package space for placement of a package; and presenting an indication of the location.

Abstract: Methods, systems and apparatus for segmenting objects are provided. A controller: receives, from one or more sensors, a 3D representation of a scene that includes an object represented by a 3D model; determines an orientation of a 2D image in the 3D representation by matching the 2D image with a corresponding region of the 3D representation; determines a first portion of the 3D representation that corresponds to a subset of the 3D model of the object from: the orientation of the 2D image in the 3D representation; and predetermined matching data representative of a matching of the 2D image with a respective corresponding region of the 3D model, each of the 3D model, the 2D image, and the predetermined matching data stored in a memory accessible to the controller; segments the first portion of the 3D representation from a second portion of the 3D representation.

Abstract: Image processing systems and methods are provided for extrinsic calibration of a plurality of image sensors. A logic circuit receives image data for an omnidirectional object from image sensors spaced apart and imaging at least a portion of a region of interest. The logic circuit combines the image data from the image sensors to generate a calibration matrix for the image sensors and to determine a matrix transformation data based on (i) reference image data and (ii) a three-dimensional model of the reference object. The logic circuit modifies the calibration matrix into an enhanced calibration matrix by applying the matrix transformation data to the calibration matrix, where the enhanced calibration matrix can be used to calibrate the plurality of image sensors.

Abstract: Dimensions of an object associated with an electro-optically readable code are estimated by aiming a handheld device at a scene containing the object supported on a base surface. A scanner on the device scans the scene over a field of view to obtain a position of a reference point of the code associated with the object, and reads the code. A dimensioning sensor on the device captures a three-dimensional (3D) point cloud of data points of the scene in automatic response to the reading of the code. A controller clusters the point cloud into data clusters, locates the reference point of the code in one of the data clusters, extracts from the point cloud the data points of the one data cluster belonging to the object, and processes the extracted data points belonging to the object to estimate the dimensions of the object.