Luis Torres

Region-based video coding using mathematical morphology

This paper presents a region-based coding algorithm for video sequences. The coding approach involves a time-recursive segmentation relying on the pixels homogeneity, a region-based motion estimation, and motion compensated contour and texture coding. This algorithm is mainly devoted to very low bit rate video coding applications. One of the important features of the approach is that no assumption is made about the sequence content. Moreover the algorithm structure leads to a scalable coding process giving various levels of quality and bit rates. The coding as well as the segmentation are controlled to regulate the bit stream. Finally, the interest of morphological tools in the content of region-based coding is extensively reviewed. >

The importance of the color information in face recognition

A common feature found in practically all technical approaches proposed for face recognition is the use of only the luminance information associated to the face image. One may wonder if this is due to the low importance of the color information in face recognition or due to other less technical reasons such as the no availability of color image database. Motivated by this reasoning, we have performed a variety of tests using a global eigen approach developed previously, which has been modified to cope with the color information. Our results show that the use of the color information embedded in a eigen approach, improve the recognition rate when compared to the same scheme which uses only the luminance information.

Distributed Monoview and Multiview Video Coding

Growing percentage of the world population now uses image and video coding technologies on a regular basis. These technologies are behind the success and quick deployment of services and products such as digital pictures, digital television, DVDs, and Internet video communications. Todays digital video coding paradigm represented by the ITU-T and MPEG standards mainly relies on a hybrid of block- based transform and interframe predictive coding approaches. In this coding framework, the encoder architecture has the task to exploit both the temporal and spatial redundancies present in the video sequence, which is a rather complex exercise. As a consequence, all standard video encoders have a much higher computational complexity than the decoder (typically five to ten times more complex), mainly due to the temporal correlation exploitation tools, notably the motion estimation process. This type of architecture is well-suited for applications where the video is encoded once and decoded many times, i.e., one-to-many topologies, such as broadcasting or video-on-demand, where the cost of the decoder is more critical than the cost of the encoder.

Distributed video coding: Selecting the most promising application scenarios

Distributed Video Coding (DVC) is a new video coding paradigm based on two major Information Theory results: the Slepian-Wolf and Wyner-Ziv theorems. Recently, practical DVC solutions have been proposed with promising results; however, there is still a need to study in a more systematic way the set of application scenarios for which DVC may bring major advantages. This paper intends to contribute for the identification of the most DVC friendly application scenarios, highlighting the expected benefits and drawbacks for each studied scenario. This selection is based on a proposed methodology which involves the characterization and clustering of the applications according to their most relevant characteristics, and their matching with the main potential DVC benefits.

An improvement on codebook search for vector quantization

Presents a simple but effective algorithm to speed up the codebook search in a vector quantization scheme when a MSE criterion is used. A considerable reduction in the number of operations is achieved. This algorithm was originally designed for image vector quantization in which the samples of the image signal (pixels) are positive, although it can be used with any positive-negative signal with only minor modifications. >

Side Information Generation for Multiview Distributed Video Coding Using a Fusion Approach

Distributed source coding (DSC) aims at achieving efficient compression by locating the source redundancies at the decoder instead of the encoder. Moreover, DSC exhibits many properties like low-complexity encoding or embedded error resilience that make it very convenient for some emerging new applications. Among the many challenging topics related to DSC there is the generation of the side information, an estimation made by the decoder of the data being decoded. In the particular field of multiview distributed video coding (multiview DVC) this side information can be generated by inter-camera or intra-camera interpolation. This paper briefly describes both techniques and proposes two approaches that combine them by evaluating the reliability of each interpolation at the pixel level

An unsupervised color image segmentation algorithm for face detection applications

This paper presents an unsupervised color segmentation technique to divide skin detected pixels into a set of homogeneous regions which can be used in face detection applications or any other application which may require color segmentation. The algorithm is carried out in a two stage processing, where the chrominance and luminance information are used consecutively. For each stage a novel algorithm which combines pixel and region based color segmentation techniques is used. The algorithm has proven to be effective under a large number of test images.

Automatic face recognition for video indexing applications

This paper presents an efficient automatic face recognition scheme useful for video indexing applications. In particular the following problem is addressed: given a set of known face images and given a complex video sequence to be indexed, find where the corresponding faces appear in the shots of the sequence. The main and final objective is to develop a tool to be used in the MPEG-7 standardization effort to help video indexing activities. Conventional face recognition schemes are not well suited for this application and alternative and more efficient schemes have to be developed. In this paper, in the context of Principal Component Analysis for face recognition, the concept of self-eigenfaces is introduced. In addition, the color information is also incorporated in the face recognition stage. The face recognition scheme is used in combination with an automatic face detection scheme which makes the overall approach highly useful. The resulting scheme is very efficient to find specific face images and to cope with the different face conditions present in a complex video sequence. Results are presented using the test sequences accepted in the MPEG-7 video content sequences set.

A simple and efficient face detection algorithm for video database applications

The objective of this work is to provide a simple and yet efficient tool to detect human faces in video sequences. This information can be very useful for many applications such as video indexing and video browsing. In particular the paper focuses on the significant improvements made to our face detection algorithm presented by Albiol, Bouman and Delp (see IEEE Int. Conference on Image Processing, Kobe, Japan, 1999). Specifically, a novel approach to retrieve skin-like homogeneous regions is presented, which is later used to retrieve face images. Good results have been obtained for a large variety of video sequences.

An automatic face detection and recognition system for video indexing applications

The objective of this work is the integration and optimization of an automatic face detection and recognition system for video indexing applications. The system is composed of a face detection stage presented previously which provides good results maintaining a low computational cost. The recognition stage is based on the Principal Components Analysis (PCA) approach which has been modified to cope with the video indexing application. After the integration of the two stages, several improvements are proposed which increase the face detection and recognition rate and the overall performance of the system. Good results have been obtained using the MPEG-7 video content set used in the MPEG-7 evaluation group.