466 research outputs found
An augmented representation of activitiy in video using semantic-context information
No full textLearning and recognizing activity in videos is an especially
important task in computer vision. However, it is hard to
perform. In this paper, we propose a new method by combining
local and global context information to extract a bag-of-wordslike
representation of a single space-time point. Each spacetime
point is described by a bag of visual words that encodes
its relationships with the remaining space-time points in the
video, defining the space-time context. Experiments on the
KTH benchmark of action recognition, show that our approach
performs accurately compared to the state-of-the-art
Semantic Shape Context for the Registration of Multiple Partial 3D Views
No full textPoint-to-point matching is a crucial stage of 3D shape analysis. It is usually solved by using descriptors that summarize the most characteristic and discriminative properties of each point. Combining local and global context information in the point descriptor is a promising approach. We propose a new approach based on what we call semantic shape context to combineeffectively local descriptors and global context information by exploiting the Bag of Words (BoW) paradigm for the representation of a single 3D point. Several local pointdescriptors are collected and quantized from the training set, by defining the visual vocabulary composed by a fixed number of visual words. Each point is then represented by a set of BoWs which encode the inter-relationship with all the other points of the object (i.e., the context). Experiments were carried out on several 3D models. The proposed approach makes fully automatic 3D registration of partial views possible, and generally outperforms stateof-the-art methods in terms of robustness and accuracy
Semantic-Context-Based Augmented Descriptor for image feature matching
No full textThis paper proposes an augmented version of local features that enhances the discriminative power of the feature without affecting its invariance to image deformations. The idea is about learning local features, aiming to estimate its semantic, which is then exploited in conjunction with the bag of words paradigm
to build an augmented feature descriptor. Basically, any local descriptor can be casted in the proposed context, and thus the approach can be easy generalized to fit in with any local approach. The semantic-context signature is a 2D histogram
which accumulates the spatial distribution of the visual words around each local feature. The obtained semantic-context component is concatenated with the local feature to generate our proposed feature descriptor. This is expected to handle
ambiguities occurring in images with multiple similar motifs and depicting slight complicated non-affine distortions, outliers, and detector errors. The approach is evaluated for two data sets. The first one is intentionally selected with images containing multiple similar regions and depicting slight non-affine distortions.
The second is the standard data set of Mikolajczyk. The valuation results showed our approach performs significantly better than expected results as well as in comparison with other methods
Molecular detection of avian pathogens in poultry red mite (Dermanyssus gallinae) in Algerian layer farms as a potential predictive tool
No full text: The poultry red mite Dermanyssus gallinae is a hematophagous ectoparasite of layer hens. Infestations with poultry red mites pose an increasing threat to the egg production industry, causing serious problems to animal health and welfare, directly or indirectly as a vector of several infectious agents. In this study, we aimed to investigate common avian pathogens in mites. The mite samples were collected from 58 poultry farms in 7 regions accounting for more than 70 % of the national egg production in Algeria. The presence of 13 avian pathogens was detected using DNA and RNA samples from mites collected. Results revealed significant associations between PRM and potential pathogens such as Escherichia coli, Salmonella enterica, fowlpox virus, and gallid herpesvirus 1. Pathogen detection in Dermanyssus gallinae could serve as an early diagnostic or a risk analysis tool for infectious diseases in poultry farms, facilitating effective disease management strategies. Despite further research being necessary to address uncertainties, such a strategy could be used to enhance the integrated management of poultry health
Samir Amin : intellectuel organique au service de l'emancipation du sud
No full textThis book on Professor Samir Amin retraces his family origins, intellectual itinerary, political struggles as well as his experience in economic policy formulation in Egypt, Mali and many other countries. The fundamentals which shaped Samir Amin's thinking, directed his life-long work and influenced his action spawned from his early discovery in high school of Marxism and Historical Materialism, used as a scientific analysis of the history of human societies. This book also highlights Samir Amin's invaluable contribution to the struggle against capitalism through his indefatigable fight to deconstruct the concepts that are used to disguise the true face of historical capitalism, which is nothing but an unabashed pursuit for accumulation and dispossession of dominated countries and peoples. Through a series of interviews with Samir Amin, the author unravels the poignant and great ideas which have been at the heart of his intellectual and political fight for the last half century. The author also provides a selection of texts which includes an exhaustive bibliography, with all published writings of Samir Amin in French. This rich work is meant for a large readership - students, researchers, teachers, political leaders and citizens who are interested in the phenomenon of globalisation and its impact on the so-called 'under-developed countries
Interview with Samir Gharib
No full textلقاء مع المؤلف المصري سمير غريب حول كتاب "راية الخيال" للكاتب إبراهيم غريب وهو كتاب عن الحركة السريالية في العالم ويربط فيه المؤلف بين التاريخ والأدب والفنون الجميلة وعلم النفس والفكر والسينما. أجرى هذا اللقاء حسن شمس الدين.An interview with Egyptian author Samir Gharib about the book The Flag of Imagination by Egyptian writer Ibrahim Gharib. The book is about the surrealist movement around the world and adopts a mix of approaches and influences from history, literature, fine arts, psychology, philosophy, and cinema. Interview conducted by Hassan Shams El Din
Descripteurs augmentés basés sur l'information sémantique contextuelle
No full textThis manuscript presents an extension of feature description and matching strategies by proposing an original approach to learn the semantic information of local features. This semantic is then exploited, in conjunction with the bag-of-words paradigm, to build a powerful feature descriptor. The approach, ended up by combining local and context information into a single descriptor, is also a generalized method for improving the performance of the local features, in terms of distinctiveness and robustness under geometric image transformations and imaging conditions. The performance of the proposed approach is evaluated on real world data sets as well as in both the 2D and 3D domains. The 2D domain application addresses the problem of image feature matching while in 3D domain, we resolve the issue of matching and alignment of multiple range images. The evaluation results showed our approach performs significantly better than expected results as well as in comparison with other methods.Les techniques de description des éléments caractéristiques d’une image sont omniprésentes dans de nombreuses applications de vision par ordinateur. Nous proposons à travers ce manuscrit une extension, pour décrire (représenter) et apparier les éléments caractéristiques des images. L’extension proposée consiste en une approche originale pour apprendre, ou estimer, la présence sémantique des éléments caractéristiques locaux dans les images. L’information sémantique obtenue est ensuite exploitée, en conjonction avec le paradigme de sac-de-mots, pour construire un descripteur d’image performant. Le descripteur résultant, est la combinaison de deux types d’informations, locale et contextuelle-sémantique. L’approche proposée peut être généralisée et adaptée à n’importe quel descripteur local d’image, pour améliorer fortement ses performances spécialement quand l’image est soumise à des conditions d’imagerie contraintes. La performance de l’approche proposée est évaluée avec des images réelles aussi bien dans les deux domaines, 2D que 3D. Nous avons abordé dans le domaine 2D, un problème lié à l’appariement des éléments caractéristiques dans des images. Dans le domaine 3D, nous avons résolu les problèmes d’appariement et alignement des vues partielles tridimensionnelles. Les résultats obtenus ont montré qu’avec notre approche, les performances sont nettement meilleures par rapport aux autres méthodes existantes
Toward semantic-shape-context-based augmented descriptor
No full textLes techniques de description des éléments caractéristiques d’une image sont omniprésentes dans de nombreuses applications de vision par ordinateur. Nous proposons à travers ce manuscrit une extension, pour décrire (représenter) et apparier les éléments caractéristiques des images. L’extension proposée consiste en une approche originale pour apprendre, ou estimer, la présence sémantique des éléments caractéristiques locaux dans les images. L’information sémantique obtenue est ensuite exploitée, en conjonction avec le paradigme de sac-de-mots, pour construire un descripteur d’image performant. Le descripteur résultant, est la combinaison de deux types d’informations, locale et contextuelle-sémantique. L’approche proposée peut être généralisée et adaptée à n’importe quel descripteur local d’image, pour améliorer fortement ses performances spécialement quand l’image est soumise à des conditions d’imagerie contraintes. La performance de l’approche proposée est évaluée avec des images réelles aussi bien dans les deux domaines, 2D que 3D. Nous avons abordé dans le domaine 2D, un problème lié à l’appariement des éléments caractéristiques dans des images. Dans le domaine 3D, nous avons résolu les problèmes d’appariement et alignement des vues partielles tridimensionnelles. Les résultats obtenus ont montré qu’avec notre approche, les performances sont nettement meilleures par rapport aux autres méthodes existantes.This manuscript presents an extension of feature description and matching strategies by proposing an original approach to learn the semantic information of local features. This semantic is then exploited, in conjunction with the bag-of-words paradigm, to build a powerful feature descriptor. The approach, ended up by combining local and context information into a single descriptor, is also a generalized method for improving the performance of the local features, in terms of distinctiveness and robustness under geometric image transformations and imaging conditions. The performance of the proposed approach is evaluated on real world data sets as well as in both the 2D and 3D domains. The 2D domain application addresses the problem of image feature matching while in 3D domain, we resolve the issue of matching and alignment of multiple range images. The evaluation results showed our approach performs significantly better than expected results as well as in comparison with other methods
Descripteurs augmentés basés sur l'information sémantique contextuelle
No full textThis manuscript presents an extension of feature description and matching strategies by proposing an original approach to learn the semantic information of local features. This semantic is then exploited, in conjunction with the bag-of-words paradigm, to build a powerful feature descriptor. The approach, ended up by combining local and context information into a single descriptor, is also a generalized method for improving the performance of the local features, in terms of distinctiveness and robustness under geometric image transformations and imaging conditions. The performance of the proposed approach is evaluated on real world data sets as well as in both the 2D and 3D domains. The 2D domain application addresses the problem of image feature matching while in 3D domain, we resolve the issue of matching and alignment of multiple range images. The evaluation results showed our approach performs significantly better than expected results as well as in comparison with other methods.Les techniques de description des éléments caractéristiques d’une image sont omniprésentes dans de nombreuses applications de vision par ordinateur. Nous proposons à travers ce manuscrit une extension, pour décrire (représenter) et apparier les éléments caractéristiques des images. L’extension proposée consiste en une approche originale pour apprendre, ou estimer, la présence sémantique des éléments caractéristiques locaux dans les images. L’information sémantique obtenue est ensuite exploitée, en conjonction avec le paradigme de sac-de-mots, pour construire un descripteur d’image performant. Le descripteur résultant, est la combinaison de deux types d’informations, locale et contextuelle-sémantique. L’approche proposée peut être généralisée et adaptée à n’importe quel descripteur local d’image, pour améliorer fortement ses performances spécialement quand l’image est soumise à des conditions d’imagerie contraintes. La performance de l’approche proposée est évaluée avec des images réelles aussi bien dans les deux domaines, 2D que 3D. Nous avons abordé dans le domaine 2D, un problème lié à l’appariement des éléments caractéristiques dans des images. Dans le domaine 3D, nous avons résolu les problèmes d’appariement et alignement des vues partielles tridimensionnelles. Les résultats obtenus ont montré qu’avec notre approche, les performances sont nettement meilleures par rapport aux autres méthodes existantes
R12. Preparation and characterization of ligand attached new 8-aminoquinoline derivative loaded nanostructured lipid carriers for liver targeting
No full textCorresponding author (Pharmaceutics and Drug delivery): Samir Senapati, [email protected]://egrove.olemiss.edu/pharm_annual_posters/1011/thumbnail.jp
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