Abstract: Examples relate to an evaluation device for re-identification and to a corresponding method, system and computer program. The evaluation device comprises processing circuitry being configured to obtain a plurality of transformed re-identification codes, each transformed re-identification code being associated with a timestamp and location information. Each transformed re-identification code is based on a similarity-preserving transformation of a re-identification code that represents at least a portion of a sample of media data, the media data originating from two or more different sources located in two or more different locations. The processing circuitry is configured to match transformed re-identification codes among the plurality of transformed re-identification codes using a similarity metric to generate one or more tuples of transformed re-identification codes that are similar according to the similarity metric.

Abstract: Examples relate to an evaluation device for re-identification and to a corresponding method, system and computer program. The evaluation device comprises processing circuitry being configured to obtain a plurality of transformed re-identification codes, each transformed re-identification code being associated with a timestamp and location information. Each transformed re-identification code is based on a similarity-preserving transformation of a re-identification code that represents at least a portion of a sample of media data, the media data originating from two or more different sources located in two or more different locations. The processing circuitry is configured to match transformed re-identification codes among the plurality of transformed re-identification codes using a similarity metric to generate one or more tuples of transformed re-identification codes that are similar according to the similarity metric.

Abstract: Examples relate to a computer-implemented method, data processing apparatus and computer program for generating three-dimensional pose-estimation data. The method comprises obtaining video data of a plurality of cameras, the video data showing a movement of one or more persons, as perceived from a plurality of angles of observation. The method comprises generating two-dimensional pose-estimation data of the one or more persons using a machine-learning model that is suitable for performing two-dimensional pose-estimation based on the video data. The method comprises generating three-dimensional pose-estimation data of the one or more persons based on the two-dimensional pose-estimation data of the one or more persons. The two-dimensional and three-dimensional pose-estimation data is defined by one or more points on the body of the one or more persons.

Abstract: Examples relate to a concept for generating training data and training a machine-learning model for use in re-identification. A computer system for generating training data for training a machine-learning model for use in re-identification comprising processing circuitry configured to obtain media data, the media data comprising a plurality of samples representing a person, an animal or an object. The processing circuitry is configured to process the media data to identify tuples of samples that represent the same person, animal or object. The processing circuitry is configured to generate the training data based on the identified tuples of samples that represent the same person, animal or object.

Abstract: Examples relate to a concept for anonymous re-identification, more specifically, but not exclusively, to systems, apparatuses, methods and computer programs for performing anonymous re-identification and for training a machine-learning model for use in anonymous re-identification. An apparatus for re-identification comprises processing circuitry configured to obtain media data via an interface. the processing circuitry is configured to generate a re-identification code representing at least a portion of the media data using a hashing algorithm. The processing circuitry is configured to transform the re-identification code using a transformation functionality to obtain a transformed re-identification code.