Nikolaos V. Boulgouris

Optimized transmission of JPEG2000 streams over wireless channels

The transmission of JPEG2000 images over wireless channels is examined using reorganization of the compressed images into error-resilient, product-coded streams. The product-code consists of Turbo-codes and Reed-Solomon codes which are optimized using an iterative process. The generation of the stream to be transmitted is performed directly using compressed JPEG2000 streams. The resulting scheme is tested for the transmission of compressed JPEG2000 images over wireless channels and is shown to outperform other algorithms which were recently proposed for the wireless transmission of images.

Real-time compressed-domain spatiotemporal segmentation and ontologies for video indexing and retrieval

In this paper, a novel algorithm is presented for the real-time, compressed-domain, unsupervised segmentation of image sequences and is applied to video indexing and retrieval. The segmentation algorithm uses motion and color information directly extracted from the MPEG-2 compressed stream. An iterative rejection scheme based on the bilinear motion model is used to effect foreground/background segmentation. Following that, meaningful foreground spatiotemporal objects are formed by initially examining the temporal consistency of the output of iterative rejection, clustering the resulting foreground macroblocks to connected regions and finally performing region tracking. Background segmentation to spatiotemporal objects is additionally performed. MPEG-7 compliant low-level descriptors describing the color, shape, position, and motion of the resulting spatiotemporal objects are extracted and are automatically mapped to appropriate intermediate-level descriptors forming a simple vocabulary termed object ontology. This, combined with a relevance feedback mechanism, allows the qualitative definition of the high-level concepts the user queries for (semantic objects, each represented by a keyword) and the retrieval of relevant video segments. Desired spatial and temporal relationships between the objects in multiple-keyword queries can also be expressed, using the shot ontology. Experimental results of the application of the segmentation algorithm to known sequences demonstrate the efficiency of the proposed segmentation approach. Sample queries reveal the potential of employing this segmentation algorithm as part of an object-based video indexing and retrieval scheme.

Gait Recognition Using Radon Transform and Linear Discriminant Analysis

A new feature extraction process is proposed for gait representation and recognition. The new system is based on the Radon transform of binary silhouettes. For each gait sequence, the transformed silhouettes are used for the computation of a template. The set of all templates is subsequently subjected to linear discriminant analysis and subspace projection. In this manner, each gait sequence is described using a low-dimensional feature vector consisting of selected Radon template coefficients. Given a test feature vector, gait recognition and verification is achieved by appropriately comparing it to feature vectors in a reference gait database. By using the new system on the Gait Challenge database, very considerable improvements in recognition performance are seen in comparison to state-of-the-art methods for gait recognition

Lossless image compression based on optimal prediction, adaptive lifting, and conditional arithmetic coding

The optimal predictors of a lifting scheme in the general n-dimensional case are obtained and applied for the lossless compression of still images using first quincunx sampling and then simple row-column sampling. In each case, the efficiency of the linear predictors is enhanced nonlinearly. Directional postprocessing is used in the quincunx case, and adaptive-length postprocessing in the row-column case. Both methods are seen to perform well. The resulting nonlinear interpolation schemes achieve extremely efficient image decorrelation. We further investigate context modeling and adaptive arithmetic coding of wavelet coefficients in a lossless compression framework. Special attention is given to the modeling contexts and the adaptation of the arithmetic coder to the actual data. Experimental evaluation shows that the best of the resulting coders produces better results than other known algorithms for multiresolution-based lossless image coding.

Wireless image transmission using turbo codes and optimal unequal error protection

A novel image transmission scheme is proposed for the communication of set partitioning in hierarchical trees image streams over wireless channels. The proposed scheme employs turbo codes and Reed-Solomon codes in order to deal effectively with burst errors. An algorithm for the optimal unequal error protection of the compressed bitstream is also proposed and applied in conjunction with an inherently more efficient technique for product code decoding. The resulting scheme is tested for the transmission of images over wireless channels. Experimental evaluation clearly demonstrates the superiority of the proposed transmission system in comparison to well-known robust coding schemes.

A family of wavelet-based stereo image coders

We propose novel algorithms for stereoscopic image coding based on the hierarchical decomposition of stereo information. The proposed schemes, based on the wavelet transform and zerotree quantization, are endowed with excellent progressive transmission capability and retain the option for perfect reconstruction of the original image pair. Experimental evaluation shows that the resulting methods produce superior results when compared with other algorithms for stereo image coding. This is achieved without introducing blocking artifacts and with the valuable additional convenience of the production of embedded bitstreams.

Human gait recognition based on matching of body components

This paper presents a novel approach for gait recognition based on the matching of body components. The human body components are studied separately and are shown to have unequal discrimination power. Several approaches are presented for the combination of the results obtained from different body components into a common distance metric for the evaluation of similarity between gait sequences. A method is also proposed for the determination of the weighting of the various body components based on their contribution to recognition performance. Using the best performing of the proposed methods, improved recognition performance is achieved.

Robust Transmission of H.264/AVC Video using Adaptive Slice Grouping and Unequal Error Protection

We present a novel scheme for the transmission of H.264/AVC video streams over lossy packet networks. The proposed scheme exploits the error resilient features of H.264/AVC codec and employs Reed-Solomon codes to protect effectively the streams. The optimal classification of macroblocks into slice groups and the optimal channel rate allocation are achieved by iterating two interdependent steps. Simulations clearly demonstrate the superiority of the proposed method over other recent algorithms for transmission of H.264/AVC streams

Compressed-domain video watermarking of MPEG streams

A new technique for watermarking of MPEG compressed video streams is proposed. The watermarking scheme operates directly in the domain of MPEG program streams. Perceptual models are used during the embedding process in order to preserve the video quality. The watermark is embedded in the compressed domain and is detected without the use of the original video sequence. Experimental evaluation demonstrates that the proposed scheme is able to withstand a variety of attacks. The resulting watermarking system is fast and reliable, and is suitable for copyright protection and real-time content authentication applications.

Gait Recognition With Shifted Energy Image and Structural Feature Extraction

In this paper, we present a novel and efficient gait recognition system. The proposed system uses two novel gait representations, i.e., the shifted energy image and the gait structural profile, which have increased robustness to some classes of structural variations. Furthermore, we introduce a novel method for the simulation of walking conditions and the generation of artificial subjects that are used for the application of linear discriminant analysis. In the decision stage, the two representations are fused. Thorough experimental evaluation, conducted using one traditional and two new databases, demonstrates the advantages of the proposed system in comparison with current state-of-the-art systems.