Deep Boosting: Layered Feature Mining for General Image Classification

Constructing effective representations is a critical but challenging problem in multimedia understanding. The traditional handcraft features often rely on domain knowledge, limiting the performances of exiting methods. This paper discusses a novel computational architecture for general image feature mining, which assembles the primitive filters (i.e. Gabor wavelets) into compositional features in a layer-wise manner. In each layer, we produce a number of base classifiers (i.e. regression stumps) associated with the generated features, and discover informative compositions by using the boosting algorithm. The output compositional features of each layer are treated as the base components to build up the next layer. Our framework is able to generate expressive image representations while inducing very discriminate functions for image classification. The experiments are conducted on several public datasets, and we demonstrate superior performances over state-of-the-art approaches.Comment: 6 pages, 4 figures, ICME 201

Wavelet based stereo images reconstruction using depth images

It is believed by many that three-dimensional (3D) television will be the next logical development toward a more natural and vivid home entertaiment experience. While classical 3D approach requires the transmission of two video streams, one for each view, 3D TV systems based on depth image rendering (DIBR) require a single stream of monoscopic images and a second stream of associated images usually termed depth images or depth maps, that contain per-pixel depth information. Depth map is a two-dimensional function that contains information about distance from camera to a certain point of the object as a function of the image coordinates. By using this depth information and the original image it is possible to reconstruct a virtual image of a nearby viewpoint by projecting the pixels of available image to their locations in 3D space and finding their position in the desired view plane. One of the most significant advantages of the DIBR is that depth maps can be coded more efficiently than two streams corresponding to left and right view of the scene, thereby reducing the bandwidth required for transmission, which makes it possible to reuse existing transmission channels for the transmission of 3D TV. This technique can also be applied for other 3D technologies such as multimedia systems. In this paper we propose an advanced wavelet domain scheme for the reconstruction of stereoscopic images, which solves some of the shortcommings of the existing methods discussed above. We perform the wavelet transform of both the luminance and depth images in order to obtain significant geometric features, which enable more sensible reconstruction of the virtual view. Motion estimation employed in our approach uses Markov random field smoothness prior for regularization of the estimated motion field. The evaluation of the proposed reconstruction method is done on two video sequences which are typically used for comparison of stereo reconstruction algorithms. The results demonstrate advantages of the proposed approach with respect to the state-of-the-art methods, in terms of both objective and subjective performance measures

Color Image Clustering using Block Truncation Algorithm

With the advancement in image capturing device, the image data been generated at high volume. If images are analyzed properly, they can reveal useful information to the human users. Content based image retrieval address the problem of retrieving images relevant to the user needs from image databases on the basis of low-level visual features that can be derived from the images. Grouping images into meaningful categories to reveal useful information is a challenging and important problem. Clustering is a data mining technique to group a set of unsupervised data based on the conceptual clustering principal: maximizing the intraclass similarity and minimizing the interclass similarity. Proposed framework focuses on color as feature. Color Moment and Block Truncation Coding (BTC) are used to extract features for image dataset. Experimental study using K-Means clustering algorithm is conducted to group the image dataset into various clusters

Overview of 3D Video: Coding Algorithms, Implementations and Standardization

Projecte final de carrera fet en col.laboració amb Linköping Institute of TechnologyEnglish: 3D technologies have aroused a great interest over the world in the last years. Television, cinema and videogames are introducing, little by little, 3D technologies into the mass market. This comes as a result of the research done in the 3D field, solving many of its limitations such as quality, contents creation or 3D displays. This thesis focus on 3D video, considering concepts that concerns the coding issues and the video formats. The aim is to provide an overview of the current state of 3D video, including the standardization and some interesting implementations and alternatives that exist. In the report necessary background information is presented in order to understand the concepts developed: compression techniques, the different video formats, their standardization and some advances or alternatives to the processes previously explained. Finally, a comparison between the different concepts is presented to complete the overview, ending with some conclusions and proposed ideas for future works.Castellano: Las tecnologías 3D han despertado un gran interés en todo el mundo en los últimos años. Televisión, cine y videojuegos están introduciendo, poco a poco, ésta tecnología en el mercado. Esto es resultado de la investigación realizada en el campo de las 3D, solucionando muchas de sus limitaciones, como la calidad, la creación de contenidos o las pantallas 3D. Este proyecto se centra en el video 3D, considerando los conceptos relacionados con la codificación y los formatos de vídeo. El objetivo es proporcionar una visión del estado actual del vídeo 3D, incluyendo los estándares y algunas de las implementaciones más interesantes que existen. En la memoria, se presenta información adicional para facilitar el seguimiento de los conceptos desarrollados: técnicas de compresión, formatos de vídeo, su estandarización y algunos avances o alternativas a los procesos explicados. Finalmente, se presentan diferentes comparaciones entre los conceptos tratados, acabando el documento con las conclusiones obtenidas e ideas propuestas para futuros trabajos.Català: Les tecnologies 3D han despertat un gran interès a tot el món en els últims anys. Televisió, cinema i videojocs estan introduint, lentament, aquesta tecnologia en el mercat. Això és resultat de la investigació portada a terme en el camp de les 3D, solucionant moltes de les seves limitacions, com la qualitat, la creació de continguts o les pantalles 3D. Aquest proyecte es centra en el video 3D, considerant els conceptes relacionats amb la codificació i els formats de video. L'objectiu és proporcionar una visió de l'estat actual del video 3D, incloent-hi els estandàrds i algunes de les implementacions més interessants que existeixen. A la memòria, es presenta informació adicional per facilitar el seguiment dels conceptes desenvolupats: tècniques de compressió, formats de video, la seva estandardització i alguns avenços o alternatives als procesos explicats. Finalment, es presenten diferents comparacions entre els conceptes tractats i les conclusions obtingudes, juntament amb propostes per a futurs treballs