1) Development of Enhanced Light Field Representation Solutions – To enable real-time streaming of Light Field (LF) content, flexible LF coded representations will be investigated, aiming to manage the massive amount of data involved and to predict the user’s movement in a fully immersive experience. For this purpose, scalable LF coding solutions will be developed aiming at supporting random access and region-of-interest (ROI) coding with high coding efficiency.2) Development of Light Field Processing Tools – The different LF capturing approaches have different spatio-angular tradeoffs and may suffer from low spatial resolution, limited depth-of-field, or high computational complexity. To overcome such limitations, advanced algorithms that can estimate accurate geometry information, create 3D models from LFs, and synthesize spatial/angular super-resolved images with high quality and efficiency are needed. To this aim, efficient LF geometry estimation and virtual view synthesis algorithms beyond conventional multi-view approaches will be investigated. Tools like segmentation and inpainting, that may especially useful for interactive LF editing, will also be considered.3) Development of Efficient Packaging Solutions for Light Field Streaming – Ultra-realistic scene rendering from LFs is a very appealing functionality for future interactive and immersive streaming services. One reason for this is the decoupling of computational cost of scene rendering from the rendered scene complexity, contrary to what happens in computer-generated 3D scenes. However, LF imaging requires a huge amount of data for proper scene rendering. To enable interactive LF rendering without requiring the whole LF to be available at the receiver, efficient packaging of the encoded LF content is needed. This would allow restricting network delivery to only the subset of the LF image that is needed to reconstruct the required view. For this to be done in an efficient way, adequate prediction mechani...

LIFESYS focus on three main scientific and technological developments: (i) novel light field content processing tools; (ii) improved scalable light field image and video coding techniques; and (iii) light field creative content generation. In this context, three main research objectives have been defined:Development of a Light Field Processing Toolbox – The light field representation format should allow a scalable representation of the content, in a manner where the various layers are defined by the author during the creative process, instead of making it a pure coding decision. For this, efficient depth-estimation and LF depth-based rendering tools will be developed, as well as LF processing tools, such as image correction, filtering and editing tools.Development of Efficient Codecs for Light Field Content – In order to enable 3D LF content to be presented on various types of displays, such as legacy displays and also newer 3D LF displays, with different characteristics in terms of spatial and view resolutions, an efficient scalable codec will be developed. New coding approaches, beyond state-of-the-art and standard-based approaches will be investigated aiming to support new scalability features opened by LF content.Development of a Light Field Authoring Application – In order to demonstrate the capabilities for the end-user and content creators of the LF technology, a showcase application will be developed that includes creative authoring tools to be used with LF content

This project aims to advance the state-of-the-art in terms of 3D holoscopic content representation, processing and coding. To enable adequate compatibility (to some extent) with legacy displays (e.g., 2D, stereoscopic, or multi-view) efficient scalable representations will be investigated. Whenever appropriate, the emerging scalable extensions of the High Efficiency Video Coding (SHVC) standard will be explored by extending these solutions to 3D holoscopic content. Additionally, since some envisaged delivery channels are critical in terms of channel errors/data losses, this project will also investigate new error control techniques that are specific for 3D holoscopic content.

The acronym of this proposal comes from the Latin and summarizes its goals: “Quis” stands for “Who is” and “Campus” refers to a delimited space. Hence, in this project we aim at research and development of a biometric recognition system able to work in completely covert conditions. The main idea is that whenever a subject enters a QUIS-CAMPUS, it is automatically recognized, using multiple biometric sources and without requiring any active participation from the subject side.

“Forensics is the application of a broad spectrum of sciences to answer questions of interest to a legal system. This may be in relation to a crime or a civil action” [Wikipedia]. Since many such questions boil down to identifying, or verifying the identity, of people allegedly involved in some action, a clear relationship exists between forensics and biometrics. Biometrics developed a number of techniques which can clearly facilitate the identification of people involved in criminal actions or civil incidents. Thus, although the two communities have traditionally often operated in relative isolation, there are many scenarios where the synergic cooperation of multimodal biometrics and forensics can be successfully applied. To address such multifaceted areas it is important to develop an interdisciplinary network with complementary competences, to foster the birth of a new community which can develop novel technological solutions to crucial issues and new challenges in forensic science.The Action will promote new partnerships, will provide education and training, will contribute to develop new standards and best practices, will produce awareness of the potential benefits of advanced technologies for evidence analysis in forensic cases and will stimulate improved mutual understanding of collaborative working models linking the academic and industrial sectors.

The main objective of this project is to design a biometric identification system to be used in uncontrolled data acquisition scenarios. In order to do this, and thus enjoy all the advantages of this type of systems mentioned above, there are four main challenges that have to be solved. These challenges can be summarized as:- Acquisition of data with enough discriminating information - This is a fundamental phase in devising any biometric application. The data acquisition setup (operating wavelength, type of illuminant, levels of luminance, number and position of illumination sources) and the protocol demanded to subjects play a crucial role in the quality of the acquired data and determine the success of the biometric recognition task. Thus, a convenient data acquisition framework should be devised in the earliest stages of the project.- Accurate biometric data segmentation - As mentioned above, traditional biometric applications, such as computer access and border control, require the user to submit a biometric in a highly controlled manner. In this kind of constrained biometric capture, users take deliberate actions to cooperate with the biometric systems, such as facing forward and standing still. This makes it easier for the system to extract the biometric information from the raw image/video data, by performing a simple segmentation. However, when the acquisition scenario is relatively uncontrolled, the acquisition system will have to be able to perform a much more sophisticated segmentation to extract the desired biometric information from the raw image/video and guarantee that it is not confused with noise, which can be quite high.- Correction of pose and illumination variations - After being able to extract the biometric data (i.e., determine its exact location) from the raw image/video data, the system has to deal with the problem of pose and illumination variations due to unconstrained biometric capture. After all, when the capture is done in an uncontrol...

The aim of the project 3D VIVANT is to capture events automatically in 3D and deliver them for realistic, interactive and immersive play back to home users-viewers. This will require the project to create, develop and integrate a comprehensive range of components from the generic technology of 3D imaging. Real and virtual 3D content will be homogeneously combined/mixed producing a novel form of rich and interactive content, defined as “3D Holoscopic content”. 3D Holoscopic imaging is a technique for creating full colour 3D optical models that exist in space independently of the viewer. The images exhibit continuous parallax throughout the viewing zone. The continuous nature of the images produced with this method eliminates the effect of 'cardboarding' (flattening of objects into discrete depth planes) and flipping (a visible effect created by moving between image fields) present in multiview stereoscopic systems. Unlike multiview stereoscopy, information about a point is contained in many different parts of the image plane. In this respect 3D Holoscopic imaging is akin to holography. However 3D Holoscopic imaging is more advantageous, since it can operate under incoherent illumination, which is in contrast with holography, and hence it allows more conventional live capture and display procedures to be adopted. Furthermore, in viewing the 3D optical model accommodation and convergence work in unison (i.e. the viewer’s eyes focus and converge to the same point) to prevent eye-strain from occurring. The 3D VIVANT project will investigate the possibility of using different technologies for capture and display of 3D content. For the capture, 3D VIVANT will take full advantage of 3D Holoscopic imaging technology, where a single camera is required. Hence in this project a world first single aperture ultra-high definition 3D Holoscopic imaging camera will be constructed which will permit live capture of 3D content. For the display, the project will take advantage of Hologr...

Biometric recognition systems target the automatic recognition of a person’s identity based on physical, physiological or behavioural characteristics (something a person is or produces). In particular, verification systems perform one to one authentication, comparing the captured biometric data with that person’s own biometric template (a mathematical representation of the biometric features extracted during the enrolment phase) previously stored in the system.One of the major vulnerabilities associated to biometric recognition systems is that once a biometric template becomes compromised, it cannot be reissued, updated or destroyed. An attacker could then gain access to all the accounts/services/applications using that same biometric trait.The main goal of the project is to create a secure multimodal biometric verification system, supporting the generation of different templates from the same biometric data, as well as cancellable templates. Furthermore, the privacy of the original biometric data needs to be guaranteed, not allowing its recovery from the stored data.State-of-the-art methods will be extended by considering a biometric verification system based on distributed source coding principles and cryptographic hash functions, to enhance security with respect to traditional biometric systems. The additional consideration of multimodal biometrics helps preventing spoof attempts by imposters while increasing recognition rates.

The main objective of this COST Action is to investigate novel technologies for unsupervised multimodal biometric authentication systems using a new generation of biometrics-enabled identity documents and smart cards, while exploring the added-value of these technologies for large-scale applications with respect to European requirements in relation to the storage, transmission, and protection of personal data

One of the main goals of this project is to develop a solution supporting the generation of different templates from the same biometric and thus supporting cancelable biometrics. Another goal is to ensure biometric privacy, not allowing the original biometric data to be recovered from the stored. For this purpose, not invertible hash functions will be used together with concepts from distributed source coding.

Specification of audiovisual representation standards (MPEG-4, MPEG-7 and MPEG-21).

The main goal of VISNET II is the provision of a working environment with appropriate integration activities and research infrastructure that will ease and stimulate the interaction and cooperation among European researchers and institutions with recognized excellence in various fields embraced by audiovisual networking technologies. The fulfilment of this objective will promote and contribute to the advances of research in this area and ultimately improve the quality and quantity of research results. Due to the high commitment of this NoE in conducting extensive dissemination activities, results will easily span across its borders, thus benefiting the whole scientific and technological communities