Abstract: A method for identifying a position of an object in a cargo space includes identifying a region of interest (ROI) from a field of view of the cargo space being captured by a camera, where the camera captures at least one of depth and color of the field of view, extracting a plurality of planes from the ROI, where the plurality of planes correspond to a geometry of the object, clustering similar and nearby planes, where the clustering is based on a weight of two or more planes of the plurality of planes and where the weight is assigned based on a property of orthogonality and a property of dimensions of two or more planes of the plurality of planes, modelling a multi-dimensional bounding box corresponding to the object based on the clustered planes, and identifying a position of the object based on a position of the multi-dimensional bounding box.

Abstract: A cargo tracking system for tracking a cargo includes a camera and a central electronic computing device. The cargo, during a loading of the cargo into a cargo space for delivering the cargo, is trackable by the camera. An information about the cargo is transmittable by the camera to the central electronic computing device. The camera is configured to estimate a size of the cargo in real time and, depending on the estimated size of the cargo and depending on a predetermined cargo size of the cargo space, the camera is configured to compute a remaining cargo size of the cargo space and to transmit the computed remaining cargo size to the central electronic computing device in real time.

Abstract: An image capturing system and methods of capturing images is provided. The system pairs an image sensor with a lighting element and light control components to improve image quality. The system further pairs one or more image sensor with one or more respective image focusing elements, thereby enabling the system to cover a variety of regions. Certain methods of the present invention include controlling light production and/or otherwise controlling when the sensor is exposed to light, what light the image sensor is exposed to, and which pathway the light must travel. By controlling light, the system and methods of the present invention controls image capture. Information availability is optimized and data processing is minimized by optimizing camera placement. Information reliability is optimized through routine assessment of the system and, when necessary, dynamically calibrating the system.

Abstract: An imaging device includes an image sensor including a rolling shutter functionality, one or more lighting elements capable of generating light at a predetermined time and duration, a light control component configured to control amount of light generated by the one or more lighting elements entering the image sensor, where the light control component is disposed between the image sensor and a lens of the imaging device; and a processing unit enabling the image sensor to function as a global shutter image sensor using the light control component, to capture at least one image of a moving object by synchronizing the light control component with light generated from the one or more lighting elements.

Abstract: A method of determining volume of a cargo space of a vehicle in real-time includes generating an initial spatial model of the cargo space using images from a plurality of cameras including cameras for capturing at least one of depth and color, positioned in and around the cargo space, where the images are stitched together into a dense point cloud in real-time, generating an updated spatial model of the cargo space using the images, upon detection of items being loaded or unloaded into the cargo space, where the updated spatial model includes changes to the cargo space, estimating a volume of loaded items in the updated spatial model, and determining a remaining volume of the cargo space based on the estimated volume of the loaded items and a total volume of the cargo space, where the total volume is calculated based on the initial spatial model.

Abstract: A method for identifying a position of an object in a cargo space includes identifying a region of interest (ROI) from a field of view of the cargo space being captured by a camera, where the camera captures at least one of depth and color of the field of view, extracting a plurality of planes from the ROI, where the plurality of planes correspond to a geometry of the object, clustering similar and nearby planes, where the clustering is based on a weight of two or more planes of the plurality of planes and where the weight is assigned based on a property of orthogonality and a property of dimensions of two or more planes of the plurality of planes, modelling a multi-dimensional bounding box corresponding to the object based on the clustered planes, and identifying a position of the object based on a position of the multi-dimensional bounding box.