Abstract: An example dimensioning device includes: a sensor to capture data representing an object; a memory configured to store: a first dimensioning function and criteria associated with the first dimensioning function; and a default dimensioning function; and a processor interconnected with the sensor and the memory, the processor configured to: in response to a dimensioning request to dimension the object, obtain the data representing the object from the sensor; select, from the first dimensioning function and the default dimensioning function, a designated dimensioning function based on the data and the criteria; call the designated dimensioning function to obtain dimensions of the object; and output the dimensions of the object.

Abstract: A method includes: capturing, via a sensor of a computing device, a three-dimensional image corresponding to an object; detecting a region of interest in the three-dimensional image, the region of interest corresponding to an obstruction; determining a depth from the sensor to the region of interest; comparing the determined depth to a threshold; determining whether to deliver the three-dimensional image to a dimensioning module, based on the comparison of the depth of the obstruction with the threshold.

Abstract: A method includes: capturing a three-dimensional image depicting an object; capturing a two-dimensional image depicting the object; determining a region of interest in the two-dimensional image, the region of interest containing the object; determining, based on the region of interest from the two-dimensional image, a quality indicator corresponding to the three-dimensional image; comparing the quality indicator to a predetermined threshold; and when the quality indicator does not satisfy the predetermined threshold, generating a positional notification.

Abstract: A computing device includes: a three-dimensional (3D) sensor configured to capture point cloud data from a field of view (FOV); an auxiliary sensor configured to capture reference depth measurements corresponding to a surface within the FOV; a controller connected with the 3D sensor and the auxiliary sensor, the controller configured to: detect a reference depth capture condition; when the reference depth capture condition satisfies a quality criterion, control the auxiliary sensor to capture a reference depth corresponding to the surface within the FOV; and initiate, based on the captured reference depth, generation of corrective data for use at the 3D sensor to capture the point cloud data.

Abstract: An example dimensioning device includes: a sensor to capture data representing an object; a memory configured to store: a first dimensioning function and criteria associated with the first dimensioning function; and a default dimensioning function; and a processor interconnected with the sensor and the memory, the processor configured to: in response to a dimensioning request to dimension the object, obtain the data representing the object from the sensor; select, from the first dimensioning function and the default dimensioning function, a designated dimensioning function based on the data and the criteria; call the designated dimensioning function to obtain dimensions of the object; and output the dimensions of the object.

Abstract: A computing device includes: a tracking sensor including a camera; a controller connected with the tracking sensor, the controller configured to: control the tracking sensor to track successive poses of the computing device in a frame of reference; detecting a plurality of dimensioning events associated with an object; in response to detecting each of the dimensioning events, generate a respective position in the frame of reference based on a current one of the poses; generate, based on the positions, an object boundary in the frame of reference; and dimension the object based on the generated object boundary.

Abstract: A computing device for dimensioning an object includes: a dimensioning subsystem configured to execute a default dimensioning method and a backup dimensioning method; a memory storing quality evaluation rules; a processor connected with the dimensioning subsystem and the memory, the processor configured to: control the dimensioning subsystem to execute a default dimensioning method to obtain default dimensioning data; compare a quality metric for the default dimensioning data to a threshold condition defined in the quality evaluation rules; when the quality metric exceeds the threshold condition, compute dimensions of the object based on the default dimensioning data; and when the quality metric does not exceed the threshold condition, control the dimensioning subsystem to execute the backup dimensioning method to obtain backup dimensioning data and compute the dimensions of the object based on the backup dimensioning data.

Abstract: A computing device includes: a three-dimensional (3D) sensor configured to capture point cloud data from a field of view (FOV); an auxiliary sensor configured to capture reference depth measurements corresponding to a surface within the FOV; a controller connected with the 3D sensor and the auxiliary sensor, the controller configured to: detect a reference depth capture condition; when the reference depth capture condition satisfies a quality criterion, control the auxiliary sensor to capture a reference depth corresponding to the surface within the FOV; and initiate, based on the captured reference depth, generation of corrective data for use at the 3D sensor to capture the point cloud data.

Abstract: A computing device for dimensioning an object includes: a dimensioning subsystem configured to execute a default dimensioning method and a backup dimensioning method; a memory storing quality evaluation rules; a processor connected with the dimensioning subsystem and the memory, the processor configured to: control the dimensioning subsystem to execute a default dimensioning method to obtain default dimensioning data; compare a quality metric for the default dimensioning data to a threshold condition defined in the quality evaluation rules; when the quality metric exceeds the threshold condition, compute dimensions of the object based on the default dimensioning data; and when the quality metric does not exceed the threshold condition, control the dimensioning subsystem to execute the backup dimensioning method to obtain backup dimensioning data and compute the dimensions of the object based on the backup dimensioning data.

Abstract: A computing device includes: a tracking sensor including a camera; a controller connected with the tracking sensor, the controller configured to: control the tracking sensor to track successive poses of the computing device in a frame of reference; detecting a plurality of dimensioning events associated with an object; in response to detecting each of the dimensioning events, generate a respective position in the frame of reference based on a current one of the poses; generate, based on the positions, an object boundary in the frame of reference; and dimension the object based on the generated object boundary.

Abstract: A device and method determines a command from a touch input. The method includes determining an application-in-use data indicative of an application being executed. The method includes receiving, by a touch sensitive input device, a touch input data including at least one of a finger use input data, a force input data, a gesture input data, and a location input data. The finger use input data relates to how the touch input data is entered. The force input data relates to a pressure applied in the touch input data. The gesture input data relates to a motion of the touch input data over time. The location input data relates to a position on the input device. The method includes determining a command based on the application-in-use data and at least one of the finger use input data, the force input data, the gesture input data, and the location input data.