Overview of the ImageCLEFphoto 2008 photographic retrieval task

ImageCLEFphoto 2008 is an ad-hoc photo retrieval task and part of the ImageCLEF evaluation campaign. This task provides both the resources and the framework necessary to perform comparative laboratory-style evaluation of visual information retrieval systems. In 2008, the evaluation task concentrated on promoting diversity within the top 20 results from a multilingual image collection. This new challenge attracted a record number of submissions: a total of 24 participating groups submitting 1,042 system runs. Some of the findings include that the choice of annotation language is almost negligible and the best runs are by combining concept and content-based retrieval methods

Overview of the 2005 cross-language image retrieval track (ImageCLEF)

The purpose of this paper is to outline efforts from the 2005 CLEF crosslanguage image retrieval campaign (ImageCLEF). The aim of this CLEF track is to explore the use of both text and content-based retrieval methods for cross-language image retrieval. Four tasks were offered in the ImageCLEF track: a ad-hoc retrieval from an historic photographic collection, ad-hoc retrieval from a medical collection, an automatic image annotation task, and a user-centered (interactive) evaluation task that is explained in the iCLEF summary. 24 research groups from a variety of backgrounds and nationalities (14 countries) participated in ImageCLEF. In this paper we describe the ImageCLEF tasks, submissions from participating groups and summarise the main fndings

The Wikipedia Image Retrieval Task

htmlabstractThe wikipedia image retrieval task at ImageCLEF provides a testbed for the system-oriented evaluation of visual information retrieval from a collection of Wikipedia images. The aim is to investigate the effectiveness of retrieval approaches that exploit textual and visual evidence in the context of a large and heterogeneous collection of images that are searched for by users with diverse information needs. This chapter presents an overview of the available test collections, summarises the retrieval approaches employed by the groups that participated in the task during the 2008 and 2009 ImageCLEF campaigns, provides an analysis of the main evaluation results, identifies best practices for effective retrieval, and discusses open issues

Overview of the ImageCLEF 2006 Photographic Retrieval and Object Annotation Tasks.

This paper describes the general photographic retrieval and object annotation tasks of the ImageCLEF 2006 evaluation campaign. These tasks provided both the resources and the framework necessary to perform comparative laboratory-style evaluation of visual information systems for image retrieval and automatic image annotation. Both tasks offered something new for 2006 and attracted a large number of submissions: 12 groups participated in ImageCLEFphoto and 3 groups in the automatic annotation task. This paper summarises these two tasks including collections used in the benchmark, the tasks proposed, a summary of submissions from participating groups and the main findings

Combining visual and textual systems within the context of user feedback

It has been proven experimentally, that a combination of textual and visual representations can improve the retrieval performance ([20], [23]). It is due to the fact, that the textual and visual feature spaces often represent complementary yet correlated aspects of the same image, thus forming a composite system. In this paper, we present a model for the combination of visual and textual sub-systems within the user feedback context. The model was inspired by the measurement utilized in quantum mechanics (QM) and the tensor product of co-occurrence (density) matrices, which represents a density matrix of the composite system in QM. It provides a sound and natural framework to seamlessly integrate multiple feature spaces by considering them as a composite system, as well as a new way of measuring the relevance of an image with respect to a context. The proposed approach takes into account both intra (via co-occurrence matrices) and inter (via tensor operator) relationships between features’ dimensions. It is also computationally cheap and scalable to large data collections. We test our approach on ImageCLEF2007photo data collection and present interesting findings

Investigating non-classical correlations between decision fused multi-modal documents

Correlation has been widely used to facilitate various information retrieval methods such as query expansion, relevance feedback, document clustering, and multi-modal fusion. Especially, correlation and independence are important issues when fusing different modalities that influence a multi-modal information retrieval process. The basic idea of correlation is that an observable can help predict or enhance another observable. In quantum mechanics, quantum correlation, called entanglement, is a sort of correlation between the observables measured in atomic-size particles when these particles are not necessarily collected in ensembles. In this paper, we examine a multimodal fusion scenario that might be similar to that encountered in physics by firstly measuring two observables (i.e., text-based relevance and image-based relevance) of a multi-modal document without counting on an ensemble of multi-modal documents already labeled in terms of these two variables. Then, we investigate the existence of non-classical correlations between pairs of multi-modal documents. Despite there are some basic differences between entanglement and classical correlation encountered in the macroscopic world, we investigate the existence of this kind of non-classical correlation through the Bell inequality violation. Here, we experimentally test several novel association methods in a small-scale experiment. However, in the current experiment we did not find any violation of the Bell inequality. Finally, we present a series of interesting discussions, which may provide theoretical and empirical insights and inspirations for future development of this direction

Overview of the ImageCLEFphoto 2007 Photographic Retrieval Task.

The general photographic ad-hoc retrieval task of the ImageCLEF 2007 evaluation campaign is described. This task provides both the resources and the framework necessary to perform comparative laboratory-style evaluation of visual information retrieval from generic photographic collections. In 2007, the evaluation objective concentrated on retrieval of lightly annotated images, a new challenge that attracted a large number of submissions: a total of 20 participating groups submitted 616 system runs. This paper summarises the components used in the benchmark, including the document collection and the search tasks, and presents an analysis of the submissions and the results

Evaluating the effort involved in relevance assessments for images

How assessors and end users judge the relevance of images has been studied in information science and information retrieval for a considerable time. The criteria by which assessors' judge relevance has been intensively studied, and there has been a large amount of work which has investigated how relevance judgments for test collections can be more cheaply generated, such as through crowd sourcing. Relatively little work has investigated the process individual assessors go through to judge the relevance of an image. In this paper, we focus on the process by which relevance is judged for images, and in particular, the degree of effort a user must expend to judge relevance for different topics. Results suggest that topic difficulty and how semantic/visual a topic is impact user performance and perceived effort

Improved ergonomic risk assessment through the combination of inertial sensors and observational methods exemplified by RULA

Zur ergonomischen Beurteilung von Arbeitsplätzen werden „ergonomic risk assessment tools“ (ERAT) verwendet. Mithilfe dieser kann die körperliche Belastung evaluiert und hinsichtlich eines biomechanischen Überlastungsrisikos bewertet werden. Dazu gehören neben Eigenangaben auch observatorische Methoden, deren Ergebnisse in Punktwerten („Scores“) zusammengefasst werden, wie z. B. die RULAMethode („rapid upper limb assessment“). Durch die technische Weiterentwicklung direkter Messmethoden können inertiale Motion-Capture-Systeme im 21. Jahrhundert präzise und kontinuierliche objektive Daten liefern. In einem neuen Ansatz wurde die observatorische Scoring-Methode RULA modifiziert und auf die digital erhobenen Daten angewendet, was differenzierte ergonomische Betrachtungen ganzer Arbeitsabläufe ermöglicht.Ergonomic risk assessment tools are used for the ergonomic assessment of workplaces. These tools can be used to evaluate the risks for biomechanical overload. In addition to self-declarations this also includes observational methods, the results of which are summarized in scores, such as the rapid upper limb assessment (RULA) method. Through the technical development of direct measurement methods, inertial motion capture systems can provide continuous objective data in the twenty-first century. In a new approach, the observational scoring method RULA has been modified and applied to digitally collected data, enabling differentiated ergonomic observations of entire workflows