4,289 research outputs found

    A Survey on Ear Biometrics

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    Recognizing people by their ear has recently received significant attention in the literature. Several reasons account for this trend: first, ear recognition does not suffer from some problems associated with other non contact biometrics, such as face recognition; second, it is the most promising candidate for combination with the face in the context of multi-pose face recognition; and third, the ear can be used for human recognition in surveillance videos where the face may be occluded completely or in part. Further, the ear appears to degrade little with age. Even though, current ear detection and recognition systems have reached a certain level of maturity, their success is limited to controlled indoor conditions. In addition to variation in illumination, other open research problems include hair occlusion; earprint forensics; ear symmetry; ear classification; and ear individuality. This paper provides a detailed survey of research conducted in ear detection and recognition. It provides an up-to-date review of the existing literature revealing the current state-of-art for not only those who are working in this area but also for those who might exploit this new approach. Furthermore, it offers insights into some unsolved ear recognition problems as well as ear databases available for researchers

    A Survey on Artificial Intelligence Techniques for Biomedical Image Analysis in Skeleton-Based Forensic Human Identification

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    This paper represents the first survey on the application of AI techniques for the analysis of biomedical images with forensic human identification purposes. Human identification is of great relevance in todayā€™s society and, in particular, in medico-legal contexts. As consequence, all technological advances that are introduced in this field can contribute to the increasing necessity for accurate and robust tools that allow for establishing and verifying human identity. We first describe the importance and applicability of forensic anthropology in many identification scenarios. Later, we present the main trends related to the application of computer vision, machine learning and soft computing techniques to the estimation of the biological profile, the identification through comparative radiography and craniofacial superimposition, traumatism and pathology analysis, as well as facial reconstruction. The potentialities and limitations of the employed approaches are described, and we conclude with a discussion about methodological issues and future research.Spanish Ministry of Science, Innovation and UniversitiesEuropean Union (EU) PGC2018-101216-B-I00Regional Government of Andalusia under grant EXAISFI P18-FR-4262Instituto de Salud Carlos IIIEuropean Union (EU) DTS18/00136European Commission H2020-MSCA-IF-2016 through the Skeleton-ID Marie Curie Individual Fellowship 746592Spanish Ministry of Science, Innovation and Universities-CDTI, Neotec program 2019 EXP-00122609/SNEO-20191236European Union (EU)Xunta de Galicia ED431G 2019/01European Union (EU) RTI2018-095894-B-I0

    Effective 3D Geometric Matching for Data Restoration and Its Forensic Application

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    3D geometric matching is the technique to detect the similar patterns among multiple objects. It is an important and fundamental problem and can facilitate many tasks in computer graphics and vision, including shape comparison and retrieval, data fusion, scene understanding and object recognition, and data restoration. For example, 3D scans of an object from different angles are matched and stitched together to form the complete geometry. In medical image analysis, the motion of deforming organs is modeled and predicted by matching a series of CT images. This problem is challenging and remains unsolved, especially when the similar patterns are 1) small and lack geometric saliency; 2) incomplete due to the occlusion of the scanning and damage of the data. We study the reliable matching algorithm that can tackle the above difficulties and its application in data restoration. Data restoration is the problem to restore the fragmented or damaged model to its original complete state. It is a new area and has direct applications in many scientific fields such as Forensics and Archeology. In this dissertation, we study novel effective geometric matching algorithms, including curve matching, surface matching, pairwise matching, multi-piece matching and template matching. We demonstrate its applications in an integrated digital pipeline of skull reassembly, skull completion, and facial reconstruction, which is developed to facilitate the state-of-the-art forensic skull/facial reconstruction processing pipeline in law enforcement

    Performance of distance-based matching algorithms in 3D facial identification

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    AbstractFacial image identification is an area of forensic sciences, where an expert provides an opinion on whether or not two or more images depict the same individual. The primary concern for facial image identification is that it must be based on sound scientific principles. The recent extensive development in 3D recording technology, which is presumed to enhance performances of identification tasks, has made essential to question conditions, under which 3D images can yield accurate and reliable results. The present paper explores the effect of mesh resolution, adequacy of selected measures of dissimilarity and number of variables employed to encode identity-specific facial features on a dataset of 528 3D face models sampled from the Fidentis 3D Face Database (Nāˆ¼2100). In order to match 3D images two quantitative approaches were tested, the first based on closest point-to-point distances computed from registered surface models and the second grounded on Procrustes distances derived from discrete 3D facial points collected manually on textured 3D facial models. The results expressed in terms of rank-1 identification rates, ROC curves and likelihood ratios show that under optimized conditions the tested algorithms have the capacity to provide very accurate and reliable results. The performance of the tested algorithms is, however, highly dependent on mesh resolution and the number of variables employed in the task. The results also show that in addition to numerical measures of dissimilarity, various 3D visualization tools can be of assistance in the decision-making

    Biometrics in forensic science: challenges, lessons and new technologies

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    Biometrics has historically found its natural mate in Forensics. The first applications found in the literature and over cited so many times, are related to biometric measurements for the identification of multiple offenders from some of their biometric and anthropometric characteristics (tenprint cards) and individualization of offender from traces found on crime-scenes (e.g. fingermarks, earmarks, bitemarks, DNA). From sir Francis Galton, to the introduction of AFIS systems in the scientific laboratories of police departments, Biometrics and Forensics have been "dating" with alternate results and outcomes. As a matter of facts there are many technologies developed under the "Biometrics umbrella" which may be optimised to better impact several Forensic scenarios and criminal investigations. At the same time, there is an almost endless list of open problems and processes in Forensics which may benefit from the introduction of tailored Biometric technologies. Joining the two disciplines, on a proper scientific ground, may only result in the success for both fields, as well as a tangible benefit for the society. A number of Forensic processes may involve Biometric-related technologies, among them: Evidence evaluation, Forensic investigation, Forensic Intelligence, Surveillance, Forensic ID management and Verification.\ud The COST Action IC1106 funded by the European Commission, is trying to better understand how Biometric and Forensics synergies can be exploited within a pan-European scientific alliance which extends its scope to partners from USA, China and Australia.\ud Several results have been already accomplished pursuing research in this direction. Notably the studies in 2D and 3D face recognition have been gradually applied to the forensic investigation process. In this paper a few solutions will be presented to match 3D face shapes along with some experimental results

    Geomatics and Forensic: Progress and Challenges

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    Since graphics hold qualitative and quantitative information of complex crime scenes, it becomes a basic key to develop hypothesis in police investigations and also to prove these hypotheses in court. Forensic analysis involves tasks of scene information mining as well as its reconstruction in order to extract elements for explanatory police test or to show forensic evidence in legal proceedings. Currently, the combination of sensors and technologies allows the integration of spatial data and the generation of virtual infographic products (orthoimages, solid images, point clouds, crossā€sections, etc.) which are extremely attractive. These products, which successfully retain accurate 3D metric information, are revolutionizing dimensional reconstruction of objects and crime scenes. Thus, it can be said that the reconstruction and 3D visualization of complex scenes are one of the main challenges for the international scientific community. To overcome this challenge, techniques related with computer vision, computer graphics and geomatics work closely. This chapter reviews a set of geomatic techniques, applied to improve infographic forensic products, and its evolution. The integration of data from different sensors whose final purpose is 3D accurate modelling is also described. As we move into a highly active research area, where there are still many uncertainties to be resolved, the final section addresses these challenges and outlines future perspectives

    Augmented reality and scene examination

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    The research presented in this thesis explores the impact of Augmented Reality on human performance, and compares this technology with Virtual Reality using a head-mounted video-feed for a variety of tasks that relate to scene examination. The motivation for the work was the question of whether Augmented Reality could provide a vehicle for training in crime scene investigation. The Augmented Reality application was developed using fiducial markers in the Windows Presentation Foundation, running on a wearable computer platform; Virtual Reality was developed using the Crytek game engine to present a photo-realistic 3D environment; and a video-feed was provided through head-mounted webcam. All media were presented through head-mounted displays of similar resolution to provide the sole source of visual information to participants in the experiments. The experiments were designed to increase the amount of mobility required to conduct the search task, i.e., from rotation in the horizontal or vertical plane through to movement around a room. In each experiment, participants were required to find objects and subsequently recall their location. It is concluded that human performance is affected not merely via the medium through which the world is perceived but moreover, the constraints governing how movement in the world is controlled

    3-D Shape Matching for Face Analysis and Recognition

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    The aims of this paper are to introduce a 3-D shape matching scheme for automatic face recognition and to demonstrate its invariance to pose and facial expressions. The core of this scheme lies on the combination of non-rigid deformation registration and statistical shape modelling. While the former matches 3-D faces regardless of facial expression variations, the latter provides a low-dimensional feature vector that describes the deformation after the shape matching process, thereby enabling robust identification of 3-D faces. In order to assist establishment of accurate dense point correspondences, an isometric embedding shape representation is introduced, which is able to transform 3-D faces to a canonical form that retains the intrinsic geometric structure and achieve shape alignment of 3-D faces independent from individualā€™s facial expression. The feasibility and effectiveness of the proposed method was investigated using standard publicly available Gavab and BU-3DFE databases, which contain faces expressions and pose variations. The performance of the system was compared with the existing benchmark approaches and it demonstrates that the proposed scheme provides a competitive solution for the face recognition task with real-world practicality

    Implications of Adult Facial Aging on Biometrics

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