http://hdl.handle.net/2117/3337 Wed, 19 Jun 2013 12:18:40 GMT 2013-06-19T12:18:40Z webmaster.bupc@upc.edu Universitat Politècnica de Catalunya. Servei de Biblioteques i Documentació no http://hdl.handle.net/2117/19316 Title: Region-based filtering of images and video sequences: a morphological viewpoint Authors: Salembier Clairon, Philippe Jean Thu, 16 May 2013 14:39:40 GMT http://hdl.handle.net/2117/19316 2013-05-16T14:39:40Z Salembier Clairon, Philippe Jean no http://hdl.handle.net/2117/18450 Title: Foreground objects segmentation for moving camera scenarios based on SCGMM Authors: Gallego, Jaime; Pardàs Feliu, Montse; Solano, Montse Abstract: In this paper we present a new system for segmenting non-rigid objects in moving camera sequences for indoor and outdoor sce narios that achieves a correct object segmentation via global MAP-MRF framework formulation for the foreground and background classification task. Our proposal, suitable for video indexation applications, receives as an input an initial segmentation of the object to segment and it consists of two region-based parametric probabilistic models to model the spatial (x,y) and color (r,g,b) domains of the foreground and background classes. Both classes rival each other in modeling the regions that appear within a dynamic region of interest that includes the foreground object to segment and also, the background regions that surrounds the object. The results presented in the paper show the correctness of the object segmentation, reducing false positive and false negative detections originated by the new background regions that appear near the region of the object Thu, 21 Mar 2013 10:45:10 GMT http://hdl.handle.net/2117/18450 2013-03-21T10:45:10Z Gallego, Jaime; Pardàs Feliu, Montse; Solano, Montse no In this paper we present a new system for segmenting non-rigid objects in moving camera sequences for indoor and outdoor sce narios that achieves a correct object segmentation via global MAP-MRF framework formulation for the foreground and background classification task. Our proposal, suitable for video indexation applications, receives as an input an initial segmentation of the object to segment and it consists of two region-based parametric probabilistic models to model the spatial (x,y) and color (r,g,b) domains of the foreground and background classes. Both classes rival each other in modeling the regions that appear within a dynamic region of interest that includes the foreground object to segment and also, the background regions that surrounds the object. The results presented in the paper show the correctness of the object segmentation, reducing false positive and false negative detections originated by the new background regions that appear near the region of the object http://hdl.handle.net/2117/17664 Title: Region-based caption text extraction Authors: León Cristóbal, Míriam; Vilaplana Besler, Verónica; Gasull Llampallas, Antoni; Marqués Acosta, Fernando Abstract: This chapter presents a method for caption text detection. The proposed method will be included in a generic indexing system dealing with other semantic concepts which are to be automatically detected as well. To have a coherent detection system, the various object detection algorithms use a common image description, a hierarchical region-based image model. The proposed method takes advantage of texture and geometric features to detect the caption text. Texture features are estimated using wavelet analysis and mainly applied for text candidate spotting. In turn, text characteristics verification relies on geometric features,which are estimated exploiting the region-based image model. Analysis of the region hierarchy provides the final caption text objects. The final step of consistency analysis for output is performed by a binarization algorithm that robustly estimates the thresholds on the caption text area of support Tue, 12 Feb 2013 14:11:11 GMT http://hdl.handle.net/2117/17664 2013-02-12T14:11:11Z León Cristóbal, Míriam; Vilaplana Besler, Verónica; Gasull Llampallas, Antoni; Marqués Acosta, Fernando no This chapter presents a method for caption text detection. The proposed method will be included in a generic indexing system dealing with other semantic concepts which are to be automatically detected as well. To have a coherent detection system, the various object detection algorithms use a common image description, a hierarchical region-based image model. The proposed method takes advantage of texture and geometric features to detect the caption text. Texture features are estimated using wavelet analysis and mainly applied for text candidate spotting. In turn, text characteristics verification relies on geometric features,which are estimated exploiting the region-based image model. Analysis of the region hierarchy provides the final caption text objects. The final step of consistency analysis for output is performed by a binarization algorithm that robustly estimates the thresholds on the caption text area of support http://hdl.handle.net/2117/16789 Title: Rich internet application for semi-automatic annotation of semantic shots on keyframes Authors: Carcel, Elisabet; Martos, Manuel; Giró Nieto, Xavier; Marqués Acosta, Fernando Abstract: This paper describes a system developed for the semiautomatic annotation of keyframes in a broadcasting company. The tool aims at assisting archivists who traditionally label every keyframe manually by suggesting them an automatic annotation that they can intuitively edit and validate. The system is valid for any domain as it uses generic MPEG-7 visual descriptors and binary SVM classifiers. The classification engine has been tested on the multiclass problem of semantic shot detection, a type of metadata used in the company to index new content ingested in the system. The detection performance has been tested in two different domains: soccer and parliament. The core engine is accessed by a Rich Internet Application via a web service. The graphical user interface allows the edition of the suggested labels with an intuitive drag and drop mechanism between rows of thumbnails, each row representing a different semantic shot class. The system has been described as complete and easy to use by the professional archivists at the company Wed, 24 Oct 2012 10:38:15 GMT http://hdl.handle.net/2117/16789 2012-10-24T10:38:15Z Carcel, Elisabet; Martos, Manuel; Giró Nieto, Xavier; Marqués Acosta, Fernando no This paper describes a system developed for the semiautomatic annotation of keyframes in a broadcasting company. The tool aims at assisting archivists who traditionally label every keyframe manually by suggesting them an automatic annotation that they can intuitively edit and validate. The system is valid for any domain as it uses generic MPEG-7 visual descriptors and binary SVM classifiers. The classification engine has been tested on the multiclass problem of semantic shot detection, a type of metadata used in the company to index new content ingested in the system. The detection performance has been tested in two different domains: soccer and parliament. The core engine is accessed by a Rich Internet Application via a web service. The graphical user interface allows the edition of the suggested labels with an intuitive drag and drop mechanism between rows of thumbnails, each row representing a different semantic shot class. The system has been described as complete and easy to use by the professional archivists at the company http://hdl.handle.net/2117/13720 Title: Person tracking Authors: Bernardin, Keni; Stiefelhagen, Rainer; Pnevmatikakis, Aristodemos; Lanz, Oswald; Brutti, Alessio; Casas Pla, Josep Ramon; Potamianos, Gerasimos Abstract: One of the most basic building blocks for the understanding of human actions and interactions is the accurate detection and tracking of persons in a scene. In constrained scenarios involving at most one subject, or in situations where persons can be confined to a controlled monitoring space or required to wear markers, sensors, or microphones, these tasks can be solved with relative ease. However, when accurate localization and tracking have to be performed in an unobtrusive or discreet fashion, using only distantly placed microphones and cameras, in a variety of natural and uncontrolled scenarios, the challenges posed are much greater. The problems faced by video analysis are those of poor or uneven illumination, low resolution, clutter or occlusion, unclean backgrounds, and multiple moving and uncooperative users that are not always easily distinguishable. Wed, 02 Nov 2011 16:29:06 GMT http://hdl.handle.net/2117/13720 2011-11-02T16:29:06Z Bernardin, Keni; Stiefelhagen, Rainer; Pnevmatikakis, Aristodemos; Lanz, Oswald; Brutti, Alessio; Casas Pla, Josep Ramon; Potamianos, Gerasimos no One of the most basic building blocks for the understanding of human actions and interactions is the accurate detection and tracking of persons in a scene. In constrained scenarios involving at most one subject, or in situations where persons can be confined to a controlled monitoring space or required to wear markers, sensors, or microphones, these tasks can be solved with relative ease. However, when accurate localization and tracking have to be performed in an unobtrusive or discreet fashion, using only distantly placed microphones and cameras, in a variety of natural and uncontrolled scenarios, the challenges posed are much greater. The problems faced by video analysis are those of poor or uneven illumination, low resolution, clutter or occlusion, unclean backgrounds, and multiple moving and uncooperative users that are not always easily distinguishable.