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International audience; B. Zhang, Y. Song, S. Guan, and Y. Zhang, "Historic Chinese Architectures Image Retrieval by SVM and Pyramid Histogram of Oriented Gradients Features," Int. J. Soft Comput., no. 2, 19–28 (2010).W.-T. Chu and M.-H. Tsai, "Visual Pattern Discovery for Architecture Image Classification and Product Image Search," Proceedings of the 2Nd ACM International Conference on Multimedia Retrieval, 1-27 (2012).G. Shalunts, Y. Haxhimusa, and R. Sablatnig, "Architectural Style Classification of Building Facade Windows," Advances in Visual Computing, 280-289 (2011)."MEX-CULTURE (Main.WebHome) – Xwiki," http://mexculture.cnam.fr/xwiki/bin/view/Main/ (01-Aug-2016)."ELAN," https://tla.mpi.nl/tools/tla-tools/elan/ (Accessed: 02-Aug-2016).L. A. Oropesa Morales, A. Montoya Obeso, R. Hernández García, S. I. Cocolán Almeda, M. S. García Vázquez, J. Benois-Pineau, L. M. Zamudio Fuentes, J. A. Martinez Nuño, and A. A. Ramírez Acosta, "Video annotations of Mexican nature in a collaborative environment," Proc. SPIE 9970, 959811-959811–12 (2015)."Universidad Carlos III de Madrid - TRECVID," 08 October 2007, http://portal.uc3m.es/portal/page/portal/grupos_investigacion/procesado_multimedia/TRECVID (27 July 2016).A. Montoya Obeso, L. A. Oropesa Morales, L. Fernando Vázquez, S. I. Cocolán Almeda, A. Stoian, M. S. García Vázquez, L. M. Z. Fuentes, J. Y. Montiel Perez, S. de la O Torres, and A. A. Ramírez Acosta, "Annotations of Mexican bullfighting videos for semantic index," Proc. SPIE 9970, 959815-959815–14 (2015).

International audience; Multimedia content production and storage in repositories are now an increasingly widespread practice. Indexing concepts for search in multimedia libraries are very useful for users of the repositories. However the search tools of content-based retrieval and automatic video tagging, still do not have great consistency. Regardless of how these systems are implemented, it is of vital importance to possess lots of videos that have concepts tagged with ground truth (training and testing sets). This paper describes a novel methodology to make complex annotations on video resources through ELAN software. The concepts are annotated and related to Mexican nature in a High Level Features (HLF) from development set of TRECVID 2014 in a collaborative environment. Based on this set, each nature concept observed is tagged on each video shot using concepts of the TRECVid 2014 dataset. We also propose new concepts, -like tropical settings, urban scenes, actions, events, weather, places for name a few. We also propose specific concepts that best describe video content of Mexican culture. We have been careful to get the database tagged with concepts of nature and ground truth. It is evident that a collaborative environment is more suitable for annotation of concepts related to ground truth and nature. As a result a Mexican nature database was built. It also is the basis for testing and training sets to automatically classify new multimedia content of Mexican nature. © (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

International audience; Human vision system is very complex and has been studied for many years specifically for purposes of efficient encoding of visual, e.g. video content from digital TV. There have been physiological and psychological evidences which indicate that viewers do not pay equal attention to all exposed visual information, but only focus on certain areas known as focus of attention (FOA) or saliency regions. In this work, we propose a novel based objective quality assessment metric, for assessing the perceptual quality of decoded video sequences affected by transmission errors and packed loses. The proposed method weights the Mean Square Error (MSE), Weighted-MSE (WMSE), according to the calculated saliency map at each pixel. Our method was validated trough subjective quality experiments.

Data visualization techniques are penetrating in various technological areas. In the field of multimedia such as information search and retrieval in multimedia archives, or digital media production and post-production, data visualization methodologies based on large graphs give an exciting alternative to conventional storyboard visualization. In this paper we develop a new approach to visualization of multimedia (video) documents based both on large graph clustering and preliminary video segmenting and indexing.

In the domain of video indexing, one of the research topics is the automatic extraction of information to reach the objective of automatically describing and organizing the content. Thinking of a video stream, different kinds of information can be taken into account, but we can suppose that most of the information is contained in the foreground objects so that number of objects, their shape, their contours and so on, can constitute a good guess for the content description. This paper describes a new approach to extract foreground objects in MPEG2 video stream, in the framework of "rough indexing paradigm" we define. This paradigm leads us to reach the purpose in near real time, nevertheless maintaining a good level of details.

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This paper presents a novel approach for an automatic partitioning of video sequences based on scene change detection and global motion estimation. The method is based on a 1D representation of images, the Bin transform, which is a discrete version of the Radon transform. Analysis of the motion and detection of the scene change are realized in the transform domain using online statistical techniques. The analysis of a 1D signal rather than the mostly used 2D image signal limits computational complexity by itself and permits fast algorithms.

In an architectural database that is to be used by architects, urbanists, sociologists, geometers, etc., querying must be simplified. The aim of this work is to retrieve the images of a building that best fit a specified point of view. Original data are provided in DXF and TIFF formats (maps and images respectively.) A loose linking between these two types of information is obtained through textural attributes. However, the same building is photographed several times and more than a single building can appear on a picture. After determining the point of view by simple `clicks' on a map, we take advantages of the geometrical description of the building in order to draw its outline. Then, the images that have been textually associated with the selected building undergo a five-steps image-processing algorithm: conversion from the RGB color- space to intensity component, Nagao filtering, oriented gradient filtering, thresholding, and correlation-based hierarchical full search matching. If the building objects are not completely masked by natural ones, the `rectangular' shapes of frontage and side walls correspond well to the sketch and the requested images are returned to the user.

Region-based coding methods can provide a solution of maximal quality for the transmission of video sequences through channels of low bit-rate due to their 'scene- adaptive' nature. Here, the visual quality of frames predicted by motion compensation on nearly semantic homogeneous regions is better than for the conventional block-based and quad-tree based methods. If the error signal is not encoded, the most bit-consuming component is the description of the regions borders and of the topology of the segmentation map. A planar graph with polygonal arcs is used to represent the geometrical form and relations of regions in each frame. A method allowing to adapt the segmentation description to the variable available bit-rate is proposed based on rate-distortion theory and constrained optimization. The method uses the concept of description layers. The 'basic' layer contains only the triplet nodes of the graph and the vertices of the highest contrast and curvature. The 'maximal enhancement' layer contains all the nodes and polygonal vertices of the segmentation graph. The choice of 'optimal' layer for each polygonal arc is done independently, minimizing Lagrangian cost function. The last one combines rate and distortion measures. The entropy estimates for the encoding of all vertices of a given arc are taken as the rate measure. The distortion measure is the total sum of squared DFD in the area delimited by the basic layer and maximal enhancement layer for a given arc. The experiments on the 420-625 CCIR videoconference sequence showed a 30 percent decrease of the bit-rate for an unnoticeable loss in quality.

We present a two-step segmentation scheme for the very low bit rate coding of general purpose video scenes. Our objective is to determine the regions of interest before the actual segmentation procedure, so as to reduce the computational overhead introduced by this relatively complex process, and to avoid the phenomenon of over-segmentation of the scene. Simulation results show that the proposed scheme results in a radical reduction of the number of discrete spatio-temporal regions, while the background is identified as one uniform region, even when it is characterized by complex global motion.

Content-based image coders become the center of attention now for the currently emerging standard MPEG-4. A method based on the spatio-temporal segmentation for motion image coding is developed in this paper. The method is designed for the sequences characterized by homogeneous global motion (camera motion) and the presence of semantic objects having proper motions. The property of the method is the fitness of the moving border to spatial contours of regions which allows for a high quality of predicted images without any error encoding.

In this paper a method for very low bit rate coding of video sequences is described. The method is based on spatio-temporal segmentation of the sequence into semantically significant regions with polygonal shapes. The motion parameters, structural description of regions and reconstruction by motion compensation error should be encoded to reconstruct high quality images at the decoder. In the coding scheme, the temporal coherence of the regions structure and of motion compensation error are taken into account in the encoding scheme to achieve a very low bit rate.