Abstract: A communication method and a communication assembly, comprising a first capturing unit configured to capture video data of a first peer in real-time, wherein the video data of the first peer comprises an identification feature a mimic expression feature; a second capturing unit configured to capture video data of a second peer in real-time; a first anonymization unit configured to modify the video data captured by the first capturing unit in real-time by replacing a characteristic of the identification feature in the video data of the first peer while substantially maintaining a characteristic of the mimic expression feature in the video data of the first peer; a first display unit of the first peer; a second display unit of the second peer; a data transfer unit configured to perform a transfer of the video data.

Abstract: Personal data processing system comprising a first device configured to capture image data including facial image data of a human being; the first device further configured to detect the facial image data of a human being, to determine a descriptor including information describing a characteristic of a mimic expression feature and a characteristic of each identification feature of a selectable subset of the plurality of identification features; the first device further configured to provide an obfuscated image with placeholder data replacing the facial image data; the first device further configured to provide the obfuscated image and the descriptor to a second device; the second device configured to perform a replacement of the placeholder data with artificial facial image data corresponding to the descriptor to produce an anonymized image.

Abstract: A method of selective image modification for protecting identities, comprises capturing a first image using an image-capturing unit of a first device and detecting, by the first device, an anonymizable object in the first image. The method further comprises determining, by the first device, that the anonymizable object is associated with a second device and modifying, by the first device, the anonymizable object in the first image by using privacy setting data received from the second device.

Abstract: A communication method and a communication assembly, comprising a first capturing unit configured to capture video data of a first peer in real-time, wherein the video data of the first peer comprises an identification feature a mimic expression feature; a second capturing unit configured to capture video data of a second peer in real-time; a first anonymization unit configured to modify the video data captured by the first capturing unit in real-time by replacing a characteristic of the identification feature in the video data of the first peer while substantially maintaining a characteristic of the mimic expression feature in the video data of the first peer; a first display unit of the first peer; a second display unit of the second peer; a data transfer unit configured to perform a transfer of the video data.

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.

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.