Reliability and effectiveness of clickthrough data for automatic image annotation

Automatic image annotation using supervised learning is performed by concept classifiers trained on labelled example images. This work proposes the use of clickthrough data collected from search logs as a source for the automatic generation of concept training data, thus avoiding the expensive manual annotation effort. We investigate and evaluate this approach using a collection of 97,628 photographic images. The results indicate that the contribution of search log based training data is positive despite their inherent noise; in particular, the combination of manual and automatically generated training data outperforms the use of manual data alone. It is therefore possible to use clickthrough data to perform large-scale image annotation with little manual annotation effort or, depending on performance, using only the automatically generated training data. An extensive presentation of the experimental results and the accompanying data can be accessed at http://olympus.ee.auth.gr/~diou/civr2009/

A new transform filtering method for image homogenization. Application to characters retrieval in optical reading

This article deals with images of nearly periodic structures represented by papers'view with dark characters on clear background . The original picture often comprises reflexion heterogeneousnesses or sheet flatness lacking which make background level undulating . We propose a suitable algorithm to solve the background homogenization problem and to allow an appropriate image segmentation . The algorithm follows from an original transform filtering approach which uses an off-centered gradient and a sliding window highpass filter .Cet article se consacre à une classe d'images à structure quasi périodique représentée par des vues de documents comportant des caractères sombres sur fond clair . L'image originale comporte souvent des hétérogénéités d'éclairage ou des défauts de planéité du document qui rendent la réflectance du fond non homogène . Nous proposons un algorithme performant capable de répondre au problème de la correction de réflectance du fond et de permettre une segmentation appropriée de l'image . Issu d'une technique originale de filtrage par transformée, il utilise l'opérateur gradient décentré ainsi qu'un filtre passe-haut à moyenne glissante

A two-dimensional deconvolution stability conditions

Deconvolution is the main prohlems of images restoration . This study deals with phenomena due to deconvolution, so stability conditions are precised about center cross convolution mask with Huang's theorem .La déconvolution est au centre des problèmes de reconstruction d'images. Dans cet article, nous présentons les phénomènes engendrés par cette opération. Nous définissons les conditions de stabilité des masques de convolution de type centré avec un voisinage en croix à partir du théorême de Huan

VITALAS at TRECVID-2009

This paper describes the participation of VITALAS in the TRECVID-2009 evaluation where we submitted runs for the High-Level Feature Extraction (HLFE) and Interactive Search tasks. For the HLFE task, we focus on the evaluation of low-level feature sets and fusion methods. The runs employ multiple low-level features based on all available modalities (visual, audio and text) and the results show that use of such features improves the retrieval eectiveness signicantly. We also use a concept score fusion approach that achieves good results with reduced low-level feature vector dimensionality. Furthermore, a weighting scheme is introduced for cluster assignment in the \bag-of-words" approach. Our runs achieved good performance compared to a baseline run and the submissions of other TRECVID-2009 participants. For the Interactive Search task, we focus on the evaluation of the integrated VITALAS system in order to gain insights into the use and eectiveness of the system's search functionalities on (the combination of) multiple modalities and study the behavior of two user groups: professional archivists and non-professional users. Our analysis indicates that both user groups submit about the same total number of queries and use the search functionalities in a similar way, but professional users save twice as many shots and examine shots deeper in the ranked retrieved list.The agreement between the TRECVID assessors and our users was quite low. In terms of the eectiveness of the dierent search modalities, similarity searches retrieve on average twice as many relevant shots as keyword searches, fused searches three times as many, while concept searches retrieve even up to ve times as many relevant shots, indicating the benets of the use of robust concept detectors in multimodal video retrieval. High-Level Feature Extraction Runs 1. A VITALAS.CERTH-ITI 1: Early fusion of all available low-level features. 2. A VITALAS.CERTH-ITI 2: Concept score fusion for ve low-level features and 100 concepts, text features and bag-of-words with color SIFT descriptor based on dense sampling. 3. A VITALAS.CERTH-ITI 3: Concept score fusion for ve low-level features and 100 concepts combined with text features. 4. A VITALAS.CERTH-ITI 4: Weighting scheme for bag-of-words based on dense sampling of the color SIFT descriptor. 5. A VITALAS.CERTH-ITI 5: Baseline run, bag-of-words based on dense sampling of the color SIFT descriptor. Interactive Search Runs 1. vitalas 1: Interactive run by professional archivists 2. vitalas 2: Interactive run by professional archivists 3. vitalas 3: Interactive run by non-professional users 4. vitalas 4: Interactive run by non-professional user

Veterinary Considerations for the Theoretical Resurrection of Extinct Species

The de-extinction of the dinosaur is a dubious possibility but its consideration brings forth some issues that are at least worthy of scientific discussion. In this review, we discuss two distinct issues that have implications for a de-extinct species such as a dinosaur: the ability, or lack thereof, to safely sedate a rare and potentially fractious animal capable of harming the veterinary staff tasked with its care; and, disease risks associated with a species that has been extinct for millions of years. To identify potential sedatives, comparative pharmacology will be needed to uncover the links between receptor pharmacology and the desired clinical outcomes of activating established alpha-2 adrenergic, opioid, and benzodiazepine receptors. Specific to disease control, it will be necessary to understand the unique susceptibility of the new species to current diseases as well as predicting their reservoir capacity for potential human and veterinary pandemic diseases. While the topics presented herein are not exhaustive, this review highlights some of the foremost research that should be conducted in order to serve the unique veterinary needs of a de-extinct species using the dinosaur as a paradigm. Addressing these issues should be considered if an intact dinosaur genome becomes available, regardless of the feasibility of dinosaur resurrection

Toward Systems Models for Obesity Prevention: A Big Role for Big Data

The relation among the various causal factors of obesity is not well understood, and there remains a lack of viable data to advance integrated, systems models of its etiology. The collection of big data has begun to allow the exploration of causal associations between behavior, built environment, and obesity-relevant health outcomes. Here, the traditional epidemiologic and emerging big data approaches used in obesity research are compared, describing the research questions, needs, and outcomes of 3 broad research domains: eating behavior, social food environments, and the built environment. Taking tangible steps at the intersection of these domains, the recent European Union project "BigO: Big data against childhood obesity" used a mobile health tool to link objective measurements of health, physical activity, and the built environment. BigO provided learning on the limitations of big data, such as privacy concerns, study sampling, and the balancing of epidemiologic domain expertise with the required technical expertise. Adopting big data approaches will facilitate the exploitation of data concerning obesity-relevant behaviors of a greater variety, which are also processed at speed, facilitated by mobile-based data collection and monitoring systems, citizen science, and artificial intelligence. These approaches will allow the field to expand from causal inference to more complex, systems-level predictive models, stimulating ambitious and effective policy interventions

Incertitude sur l'analyse des contraintes par diffraction des rayons X

In this study, we have developped a method to estimate the value of the errors committed during the stress analysis by X-Ray diffraction. We have cherched the non bias of the proposed estimators and the validity of all the made hypothesis by fifty stress determinations. We have equally established a criterion to choose the number of the ψ angles, with reference to the wished precision, and another criterion to check the good position of the sample with respect to the goniometric centre of the diffractometer.Dans cette étude, nous avons développé une méthode d'estimation de la valeur des erreurs de mesure commises lors de l'analyse des contraintes par diffraction des rayons X. Nous avons vérifié à partir de cinquante déterminations des contraintes le non-biais des estimateurs proposés, ainsi que toutes les hypothèses faites pour établir ces estimateurs. Nous avons également établi un critère de choix du nombre et des valeurs des angles d'incidence ψ en fonction de la précision de mesure souhaitée, ainsi qu'un critère de bon positionnement de l'échantillon par rapport au centre goniométrique du diffractomètre

Are clickthrough data reliable as image annotations?

We examine the reliability of clickthrough data as concept-based image annotations, by comparing them against manual annotations, for different concept categories. Our analysis shows that, for many concepts, the image annotations generated by using clickthrough data are reliable, with up to 90% of true positives in the automatically annotated images compared to the manual ground truth. Concept categories, though, do not provide additional evidence about the types of concepts for which clickthrough-based image annotation performs well

Fractal Nature of Chewing Sounds

monitoring has been investigated by many researchers. For this purpose, one of the most promising modalities is the acoustic signal captured by a common microphone placed inside the outer ear canal. Various chewing detection algorithms for this type of signals exist in the literature. In this work, we perform a systematic analysis of the fractal nature of chewing sounds, and find that the Fractal Dimension is substantially different between chewing and talking. This holds even for severely down-sampled versions of the recordings. We derive chewing detectors based on the the fractal dimension of the recorded signals that can clearly discriminate chewing from non-chewing sounds. We experimentally evaluate snacking detection based on the proposed chewing detector, and we compare our approach against well known counterparts. Experimental results on a large dataset of 10 subjects and total recordings duration of more than 8 hours demonstrate the high effectiveness of our method. Furthermore, there exists indication that discrimination between different properties (such as crispness) is possible