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We consider the problem of compressing discrete memory less data sequences for the purpose of similarity identification, first studied by Ahlswede et al. (1997). In this setting, a source sequence is compressed, where the goal is to be able to identify whether the original source sequence is similar to another given sequence (called the query sequence). There is no requirement that the source will...
In recent years, hashing techniques are becoming overwhelmingly popular for their high efficiency in handling large-scale computer vision applications. It has been shown that hashing techniques which leverage supervised information can significantly enhance performance, and thus greatly benefit visual search tasks. Typically, a modern hashing method uses a set of hash functions to compress data samples...
The amount of generated RDF data has grown impressively over the last decade, promoting compression as an essential tool for storage and exchange. RDF compression techniques leverage syntactic and semantic redundancies, but structural repetitions are not always addressed effectively. This paper first shows two schema-based sources of redundancy underlying to the schema-relaxed nature of RDF. Then,...
"View-plus-depth" is a popular 3D image representation format, in which the color 2D image is augmented with a gray-scale image representing the scene depth map aligned with the color pixels. In this paper, we propose a novel depth map compression method aimed at finding an optimal spatial depth scale and down-sampling (sparsifying) the depth image over it. The down-sampled depth image is...
Recent years have seen the upraising of a new type of processors strongly relying on the Single Instruction, Multiple Data (SIMD) architectural principle. The main idea behind SIMD computing is to apply a flow of instructions to multiple pieces of data in parallel and synchronously. This permits the execution of thousands of operations in parallel, achieving higher computational performance than with...
The issue of backwards compatible image and video coding gained some attention in both MPEG and JPEG, let it be as extension for HEVC, let it be as the JPEG XT standardization initiative of the SC29WG1 committee. The coding systems work all on the principle of a base layer operating in the low-dynamic range regime, using a tone-mapped version of the HDR material as input, and an extension layer invisible...
The first step in an image retrieval pipeline consists of comparing global descriptors from a large database to find a short list of candidate matching images. The more compact the global descriptor, the faster the descriptors can be compared for matching. State-of-the-art global descriptors based on Fisher Vectors are represented with tens of thousands of floating point numbers. While there is significant...
Fractional-pel motion compensation is very good at improving video coding efficiency, especially for camera-captured content. But for screen content, which is obtained from a computer desktop, motion vectors with integer-precision may be enough to represent the motion in different pictures. Using fractional-pel motion compensation for such content is a waste of bits. Thus, adaptive motion compensation...
Compressed Sensing (CS) has been widely used for multimedia processing to reduce the number of the measurements required to acquire signals that are spare or compressible sparse in some basis. CS provides good quality of the restored signal even when the signal is not completely sparse and even also at high compression ratio. However, classical CS assumes that the measurements are real-valued and...
Dube and Beaudoin have proposed a technique of lossless data compression called compression via substring enumeration (CSE) for a binary source alphabet. Dube and Yokoo proved that CSE has a linear complexity both in time and in space worst-case performance for the length of string to be encoded. Dubé and Yokoo have specified appropriate predictors of the uniform and combinatorial prediction models...
In this work, for a given a set of code vector assignments to an input by a multistage residual vector quantizer RVQ [1], Bayesian framework is formulated to find the most probable class membership of the input. Furthermore, Markov structure is also used to improve the memory cost of the classification.
It is well known that the Karhunen -- Loeve Transform (KLT) diagonalizes the covariance matrix and gives the optimal energy compaction. Since the real covariance matrix may not be obtained in video compression, we consider a covariance model that can be constructed without extra cost. In this work, a covariance model based on a graph is considered for temporal transforms of videos. The relation between...
Current compression systems incorporate a data model, however formed, deeply into the coding process, leading to difficulties of an architectural nature. This work contributes an alternative "Model-Code Separation" architecture for general compression, based on model-free coding and iterative message-passing algorithms over graphical models representing the modeling and coding aspects of...
We present a new image compression or intra-frame coding approach, which is based on a quadrilateral-shape polygon unit for reducing spatial redundancies. The proposed method partitions raw video frame data to quadrilateral-shape polygon unit first, and then predicts, transforms, quantizes and compresses the partitioned quadrilateral polygon. Performance evaluations have shown that the proposed method...
Visual text information is a descriptive part of many images that can be used to perform mobile visual search (MVS) with particularly small queries. In this paper, we propose a system that uses word patch descriptors for retrieving images containing visual text. A random sampling method is used to find duplicate word patches in the database and reduce the database size. The system achieves comparable...
Crash test simulation is a key component of automotive research and development. Managing simulation output has become a huge task, due to the number of simulations and the size of their generated output. Consequently, simulation data management systems (SDMS) were deployed. SDMS provide access to large numbers of simulation results, and therefore, using compression methods to exploit relations between...
Current compression solutions either use a limited size locality-based context or the entire input, to which the compressors adapt. This results in suboptimal compression effectiveness due to missing similarities further apart in the former case, or due to too generic adaptation. There are many deduplication and near deduplication systems that search for similarity across the entire input. Although...
Probability estimation is an elementary building block of every statistical data compression algorithm. In practice probability estimation is often based on relative letter frequencies which get scaled down, when their sum is too large. Such algorithms are attractive in terms of memory requirements, running time and practical performance. However, there still is a lack of theoretical understanding...
Given a file T, and the Huffman encoding of its elements, we present a data structure that enables direct access to the i-th element of T by reordering the bits of the compressed file and using some additional space. When compared to a Wavelet tree for Huffman Codes, our different reordering of the bits requires less additional storage overhead by reducing the need for auxiliary rank structures, while...
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