Quantization is a process that maps a continous or discrete set of values into approximations that belong to a smaller set. Quantization is a lossy: some information about the original data is lost in the process. The key to a successful quantization is therefore the selection of an error criterion – such as entropy and signal-to-noise ratio – and the development of optimal quantizers for this criterion.

Quantization

A method and system are provided for tagging, indexing, searching, retrieving, manipulating, and editing video images on a wide area network such as the Internet. A first set of methods is provided for enabling users to add bookmarks to multimedia files, such as movies, and audio files, such as music. The multimedia bookmark facilitates the searching of portions or segments of multimedia files, particularly when used in conjunction with a search engine. Additional methods are provided that reformat a video image for use on a variety of devices that have a wide range of resolutions by selecting some material (in the case of smaller resolutions) or more material (in the case of larger resolutions) from the same multimedia file. Still more methods are provided for interrogating images that contain textual information (in graphical form) so that the text may be copied to a tag or bookmark that can itself be indexed and searched to facilitate later retrieval via a search engine.

System and method for indexing, searching, identifying, and editing portions of electronic multimedia files

This paper introduces MorphoSys, a reconfigurable computing system developed to investigate the effectiveness of combining reconfigurable hardware with general-purpose processors for word-level, computation-intensive applications. MorphoSys is a coarse-grain, integrated, and reconfigurable system-on-chip, targeted at high-throughput and data-parallel applications. It is comprised of a reconfigurable array of processing cells, a modified RISC processor core, and an efficient memory interface unit. This paper describes the MorphoSys architecture, including the reconfigurable processor array, the control processor, and data and configuration memories. The suitability of MorphoSys for the target application domain is then illustrated with examples such as video compression, data encryption and target recognition. Performance evaluation of these applications indicates improvements of up to an order of magnitude (or more) on MorphoSys, in comparison with other systems.

MorphoSys: an integrated reconfigurable system for data-parallel and computation-intensive applications

We propose a novel and simple fast block-matching algorithm (BMA), called adaptive rood pattern search (ARPS), which consists of two sequential search stages: (1) initial search and (2) refined local search. For each macroblock (MB), the initial search is performed only once at the beginning in order to find a good starting point for the follow-up refined local search. By doing so, unnecessary intermediate search and the risk of being trapped into local minimum matching error points could be greatly reduced in long search case. For the initial search stage, an adaptive rood pattern (ARP) is proposed, and the ARP's size is dynamically determined for each MB, based on the available motion vectors (MVs) of the neighboring MBs. In the refined local search stage, a unit-size rood pattern (URP) is exploited repeatedly, and unrestrictedly, until the final MV is found. To further speed up the search, zero-motion prejudgment (ZMP) is incorporated in our method, which is particularly beneficial to those video sequences containing small motion contents. Extensive experiments conducted based on the MPEG-4 Verification Model (VM) encoding platform show that the search speed of our proposed ARPS-ZMP is about two to three times faster than that of the diamond search (DS), and our method even achieves higher peak signal-to-noise ratio (PSNR) particularly for those video sequences containing large and/or complex motion contents.

Adaptive rood pattern search for fast block-matching motion estimation

The correspondence presents a fast exhaustive search algorithm for motion estimation. The basic idea is to obtain the best estimate of the motion vectors by successively eliminating the search positions in the search window and thus decreasing the number of matching evaluations that require very intensive computations. Simulation results demonstrate that although the performance of the proposed algorithm is the same as that using the exhaustive search, the computation time has been reduced significantly. >

Successive elimination algorithm for motion estimation

The block-matching motion estimation is the most popular method for motion-compensated coding of image sequence. A VLSI architecture for implementing a full-search block-matching algorithm is presented. Based on a systolic array processor and shift register arrays with programmable length, the proposed architecture has the following advantages: it allows serial data input to save the pin counts but performs parallel processing; it is flexible in adaptation to the dimensional change of the search area via simple control; it can operate in real time for videoconference applications; and it is simple and modular in design, and thus is suitable for VLSI implementation. >

VLSI architecture for block-matching motion estimation algorithm

In memoryless vector quantization (VQ) for images, each block is quantized independently and its corresponding index is sent to the decoder. This paper presents a new lossless algorithm that exploits the interblock correlation in the index domain. We compare the current index with previous indices in a predefined search path, and then send the corresponding search order to the decoder. The new algorithm achieves significant reduction of bit rates without introducing extra coding distortion when compared to memoryless VQ. It is very simple and computationally efficient.

Lossless compression of VQ index with search-order coding

A new motion estimation algorithm that exploits the motion correlation of neighbor blocks in temporal and spatial directions is presented. Preliminary results indicate that this algorithm achieves significant savings on computation time and the amount of side information on motion vectors.

Motion estimation algorithm using interblock correlation

The encoding of vector quantization (VQ) needs expensive computation for searching the closest codevector to the input vector. This paper presents several fast encoding algorithms based on multiple triangle inequalities and wavelet transform to overcome this problem. The multiple triangle inequalities confine a search range using the intersection of search areas generated from several control vectors. A systematic way for designing the control vectors is also presented. The wavelet transform combined with the partial distance elimination is used to reduce the computational complexity of the distance calculation of vectors. The proposed algorithms provide the same coding quality as the full search method. The experimental results indicate that the new algorithms perform more efficiently than existing algorithms.

Fast search algorithms for vector quantization of images using multiple triangle inequalities and wavelet transform

This paper presents a human action recognition method using histogram of oriented gradient (HOG) of motion history image (MHI). First, the proposed method generates MHI with differential images which are obtained by frame difference of successive frames of a video. The histogram of oriented gradient (HOG) of the MHI is then computed. Finally, support vector machine (SVM) is applied to train an action classifier using the HOG features. We discovered that the new method improves recognition rate significantly. Moreover, our algorithm does not require the generation process of human silhouette, and therefore the performance is also increased. Experimental results are provided to show the promising performance of the proposed method.

Chaur-Heh Hsieh

Papers

VLSI architecture for block-matching motion estimation algorithm

Lossless compression of VQ index with search-order coding

Motion estimation algorithm using interblock correlation

Fast search algorithms for vector quantization of images using multiple triangle inequalities and wavelet transform

Human Action Recognition Using Histogram of Oriented Gradient of Motion History Image