Tomtom Global Content B.v.

Other

Arkadiusz Wysocki

Marcin Michal Kmiecik

Rafal Jan Gliszczynski

James Edward Hagan

Lukasz Piotr Taborowski

A method of processing camera data of a mobile mapping system is disclosed. In at least one embodiment, the method includes a) obtaining camera data from at least one camera of the mobile mapping system, b) detecting at least one region in the camera data, c) applying a compression technique on the camera data in a first region, and d) obtaining range sensor data from at least a first range sensor. The range sensor data may at least partially correspond to the camera data. Also, in at least one embodiment, b) includes using the range sensor data to identify the at least one region in the camera data.

Method of using laser scanned point clouds to create selective compression masks

A method of creating an audience map comprising the steps of; receiving a focus point comprising location data defining a geographical location; receiving trace data defining at least one geographical location of a potential viewer; determining a field of view which represents a region within which a potential viewer could see the focus point; projecting the field of view from either; (i) the focus point and determining whether the or each geographical location of the trace data falls within the field of view of the focus point and recording occurrences thereof; or (ii) the or each of the geographical locations of the potential viewer and determining whether the geographical location of the focus point falls within the field of view of the or each of the geographical locations of the potential viewer and recording occurrences thereof; and generating an audience map based on the recorded occurrences.

Method of creating an audience map

A method of detecting objects from terrestrial based mobile mapping data is disclosed, wherein the terrestrial based mobile mapping data has been captured by way of a terrestrial based mobile mapping vehicle driving on a road having a driving direction, the mobile mapping data including laser scanner data, source images obtained by at least one camera and position and orientation data of the vehicle, wherein the laser scanner data includes laser points, each laser point having associated position and orientation data, and each source image comprises associated position and orientation data. In at least one embodiment, the method includes: retrieving a position and orientation of the vehicle; filtering the laser scanner data in dependence of the position and orientation of the vehicle to obtain laser points corresponding to regions of interest; retrieving a source image associated with the position and orientation of the vehicle; mapping the laser points corresponding to regions of interest to image coordinates of the source image to generate a recognition mask; combining the recognition mask and the source image to obtain candidate 3D images representative of possible objects within the regions of interest; and, detecting a group of objects from the candidate 3D images. By combining image recognition and laser scanner recognition the detection rate can be increased to a very high percentage, thereby substantially reducing human effort. Furthermore, the generating of regions of interest in the laser data, enables a significant reduction of the processing power and/or the processing time needed to detect the objects in the images.

Method and apparatus for detecting objects from terrestrial based mobile mapping data

A method of identifying a planar object in source images is disclosed. In at least one embodiment, the method includes: retrieving a first source image obtained by a first terrestrial based camera; retrieving a second source image obtained by a second terrestrial based camera; retrieving position data associated with the first and second source image; retrieving orientation data associated with the first and second source image; performing a looking axis rotation transformation on the first and second source image by use of the associated position data and orientation data to obtain first and second intermediate images, wherein the first and second intermediate images have an identical looking axis; performing a radial logarithmic space transformation on the first and second intermediate images to obtain first and second radial logarithmic data images; detecting an area in the first image potentially being a planar object; comparing the potential planar object having similar dimensions in the second radial logarithmic data image and similar rgb characteristics; and finally, identifying the area as a planar object and determining its position. At least one embodiment of the method enables the engineer to detect very efficiently planar perpendicular objects in subsequent images.

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Lodz, Poland

Arkadiusz Wysocki