Scene representation for object monitoring

In robotics, having a 3D representation of the environment where a robot is working can be very useful. In real-life scenarios, this environment is constantly changing for example by human interaction, external agents or by the robot itself. Thus, the representation needs to be constantly updated and extended to account for these dynamic scene changes. In this work we face the problem of representing the scene where a robot is acting. Moreover, we ought to improve this representation by reusing the information obtained in previous scenes. Our goal is to build a method to represent a scene and to update it while changes are produced. In order to achieve that, different aspects of computer vision such as space representation or feature tracking are discussed

Forensic processing of false identity and travel documents to produce intelligence: a novel approach to assist in fighting organized crime

The production and use of false identity and travel documents in organized crime represent a serious and evolving threat. However, a case-by-case perspective, thus suffering from linkage blindness and a limited analysis capacity, essentially drives the present-day fight against this criminal problem. To assist in overcoming these limitations, a process model was developed using a forensic perspective. It guides the systematic analysis and management of seized false documents to generate forensic intelligence that supports strategic and tactical decision-making in an intelligence-led policing approach. The model is articulated on a three-level architecture that aims to assist in detecting and following-up on general trends, production methods and links between cases or series. Using analyses of a large dataset of counterfeit and forged identity and travel documents, it is possible to illustrate the model, its three levels and their contribution. Examples will point out how the proposed approach assists in detecting emerging trends, in evaluating the black market's degree of structure, in uncovering criminal networks, in monitoring the quality of false documents, and in identifying their weaknesses to orient the conception of more secured travel and identity documents. The process model proposed is thought to have a general application in forensic science and can readily be transposed to other fields of study.

The importance of distinguishing information from evidence/observations when formulating propositions

The value of forensic results crucially depends on the propositions and the information under which they are evaluated. For example, if a full single DNA profile for a contemporary marker system matching the profile of Mr A is assessed, given the propositions that the DNA came from Mr A and given it came from an unknown person, the strength of evidence can be overwhelming (e.g., in the order of a billion). In contrast, if we assess the same result given that the DNA came from Mr A and given it came from his twin brother (i.e., a person with the same DNA profile), the strength of evidence will be 1, and therefore neutral, unhelpful and irrelevant 1 to the case at hand. While this understanding is probably uncontroversial and obvious to most, if not all practitioners dealing with DNA evidence, the practical precept of not specifying an alternative source with the same characteristics as the one considered under the first proposition may be much less clear in other circumstances. During discussions with colleagues and trainees, cases have come to our attention where forensic scientists have difficulty with the formulation of propositions. It is particularly common to observe that results (e.g., observations) are included in the propositions, whereas-as argued throughout this note-they should not be. A typical example could be a case where a shoe-mark with a logo and the general pattern characteristics of a Nike Air Jordan shoe is found at the scene of a crime. A Nike Air Jordan shoe is then seized at Mr A's house and control prints of this shoe compared to the mark. The results (e.g., a trace with this general pattern and acquired characteristics corresponding to the sole of Mr A's shoe) are then evaluated given the propositions 'The mark was left by Mr A's Nike Air Jordan shoe-sole' and 'The mark was left by an unknown Nike Air Jordan shoe'. As a consequence, the footwear examiner will not evaluate part of the observations (i.e., the mark presents the general pattern of a Nike Air Jordan) whereas they can be highly informative. Such examples can be found in all forensic disciplines. In this article, we present a few such examples and discuss aspects that will help forensic scientists with the formulation of propositions. In particular, we emphasise on the usefulness of notation to distinguish results that forensic scientists should evaluate from case information that the Court will evaluate.