Enhanced 2D/3D Approaches Based on Relevance Index for 3D-Shape Retrieval

International audienceWe present a new approach for 3D model indexing and retrieval using 2D/3D shape descriptors based on silhouettes or depth-buffer images. To take into account the dispersion of information in the views, we associate to each view a relevance index which will be afterward used in the dissimilarity computation. The performance of this new approach is evaluated on the Princeton 3D Shape Benchmark database

View subspaces for indexing and retrieval of 3D models

View-based indexing schemes for 3D object retrieval are gaining popularity since they provide good retrieval results. These schemes are coherent with the theory that humans recognize objects based on their 2D appearances. The viewbased techniques also allow users to search with various queries such as binary images, range images and even 2D sketches. The previous view-based techniques use classical 2D shape descriptors such as Fourier invariants, Zernike moments, Scale Invariant Feature Transform-based local features and 2D Digital Fourier Transform coefficients. These methods describe each object independent of others. In this work, we explore data driven subspace models, such as Principal Component Analysis, Independent Component Analysis and Nonnegative Matrix Factorization to describe the shape information of the views. We treat the depth images obtained from various points of the view sphere as 2D intensity images and train a subspace to extract the inherent structure of the views within a database. We also show the benefit of categorizing shapes according to their eigenvalue spread. Both the shape categorization and data-driven feature set conjectures are tested on the PSB database and compared with the competitor view-based 3D shape retrieval algorithmsComment: Three-Dimensional Image Processing (3DIP) and Applications (Proceedings Volume) Proceedings of SPIE Volume: 7526 Editor(s): Atilla M. Baskurt ISBN: 9780819479198 Date: 2 February 201

CHORUS Deliverable 2.1: State of the Art on Multimedia Search Engines

Based on the information provided by European projects and national initiatives related to multimedia search as well as domains experts that participated in the CHORUS Think-thanks and workshops, this document reports on the state of the art related to multimedia content search from, a technical, and socio-economic perspective. The technical perspective includes an up to date view on content based indexing and retrieval technologies, multimedia search in the context of mobile devices and peer-to-peer networks, and an overview of current evaluation and benchmark inititiatives to measure the performance of multimedia search engines. From a socio-economic perspective we inventorize the impact and legal consequences of these technical advances and point out future directions of research

Local wavelet features for statistical object classification and localisation

This article presents a system for texture-based probabilistic classification and localisation of 3D objects in 2D digital images and discusses selected applications. The objects are described by local feature vectors computed using the wavelet transform. In the training phase, object features are statistically modelled as normal density functions. In the recognition phase, a maximisation algorithm compares the learned density functions with the feature vectors extracted from a real scene and yields the classes and poses of objects found in it. Experiments carried out on a real dataset of over 40000 images demonstrate the robustness of the system in terms of classification and localisation accuracy. Finally, two important application scenarios are discussed, namely classification of museum artefacts and classification of metallography images

CHORUS Deliverable 2.2: Second report - identification of multi-disciplinary key issues for gap analysis toward EU multimedia search engines roadmap

After addressing the state-of-the-art during the first year of Chorus and establishing the existing landscape in multimedia search engines, we have identified and analyzed gaps within European research effort during our second year. In this period we focused on three directions, notably technological issues, user-centred issues and use-cases and socio- economic and legal aspects. These were assessed by two central studies: firstly, a concerted vision of functional breakdown of generic multimedia search engine, and secondly, a representative use-cases descriptions with the related discussion on requirement for technological challenges. Both studies have been carried out in cooperation and consultation with the community at large through EC concertation meetings (multimedia search engines cluster), several meetings with our Think-Tank, presentations in international conferences, and surveys addressed to EU projects coordinators as well as National initiatives coordinators. Based on the obtained feedback we identified two types of gaps, namely core technological gaps that involve research challenges, and “enablers”, which are not necessarily technical research challenges, but have impact on innovation progress. New socio-economic trends are presented as well as emerging legal challenges

Cloud-Based Benchmarking of Medical Image Analysis

Medical imagin

Mobile 2D and 3D Spatial Query Techniques for the Geospatial Web

The increasing availability of abundant geographically referenced information in the Geospatial Web provides a variety of opportunities for developing value-added LBS applications. However, large data volumes of the Geospatial Web and small mobile device displays impose a data visualization problem, as the amount of searchable information overwhelms the display when too many query results are returned. Excessive returned results clutter the mobile display, making it harder for users to prioritize information and causes confusion and usability problems. Mobile Spatial Interaction (MSI) research into this “information overload” problem is ongoing where map personalization and other semantic based filtering mechanisms are essential to de-clutter and adapt the exploration of the real-world to the processing/display limitations of mobile devices. In this thesis, we propose that another way to filter this information is to intelligently refine the search space. 3DQ (3-Dimensional Query) is our novel MSI prototype for information discovery on today’s location and orientation-aware smartphones within 3D Geospatial Web environments. Our application incorporates human interactions (interpreted from embedded sensors) in the geospatial query process by determining the shape of their actual visibility space as a query “window” in a spatial database, e.g. Isovist in 2D and Threat Dome in 3D. This effectively applies hidden query removal (HQR) functionality in 360º 3D that takes into account both the horizontal and vertical dimensions when calculating the 3D search space, significantly reducing display clutter and information overload on mobile devices. The effect is a more accurate and expected search result for mobile LBS applications by returning information on only those objects visible within a user’s 3D field-of-view. ii

Data-Driven Shape Analysis and Processing

Data-driven methods play an increasingly important role in discovering geometric, structural, and semantic relationships between 3D shapes in collections, and applying this analysis to support intelligent modeling, editing, and visualization of geometric data. In contrast to traditional approaches, a key feature of data-driven approaches is that they aggregate information from a collection of shapes to improve the analysis and processing of individual shapes. In addition, they are able to learn models that reason about properties and relationships of shapes without relying on hard-coded rules or explicitly programmed instructions. We provide an overview of the main concepts and components of these techniques, and discuss their application to shape classification, segmentation, matching, reconstruction, modeling and exploration, as well as scene analysis and synthesis, through reviewing the literature and relating the existing works with both qualitative and numerical comparisons. We conclude our report with ideas that can inspire future research in data-driven shape analysis and processing.Comment: 10 pages, 19 figure

Mobile 2D and 3D Spatial Query Techniques for the Geospatial Web

The increasing availability of abundant geographically referenced information in the Geospatial Web provides a variety of opportunities for developing value-added LBS applications. However, large data volumes of the Geospatial Web and small mobile device displays impose a data visualization problem, as the amount of searchable information overwhelms the display when too many query results are returned. Excessive returned results clutter the mobile display, making it harder for users to prioritize information and causes confusion and usability problems. Mobile Spatial Interaction (MSI) research into this “information overload” problem is ongoing where map personalization and other semantic based filtering mechanisms are essential to de-clutter and adapt the exploration of the real-world to the processing/display limitations of mobile devices. In this thesis, we propose that another way to filter this information is to intelligently refine the search space. 3DQ (3-Dimensional Query) is our novel MSI prototype for information discovery on today’s location and orientation-aware smartphones within 3D Geospatial Web environments. Our application incorporates human interactions (interpreted from embedded sensors) in the geospatial query process by determining the shape of their actual visibility space as a query “window” in a spatial database, e.g. Isovist in 2D and Threat Dome in 3D. This effectively applies hidden query removal (HQR) functionality in 360º 3D that takes into account both the horizontal and vertical dimensions when calculating the 3D search space, significantly reducing display clutter and information overload on mobile devices. The effect is a more accurate and expected search result for mobile LBS applications by returning information on only those objects visible within a user’s 3D field-of-view