Codebook

About: Codebook is a research topic. Over the lifetime, 8492 publications have been published within this topic receiving 115995 citations.

An integrated circuit design for pruned tree-search vector quantization encoding with an off-chip controller

Abstract: The design of an encoder for pruned tree-search vector quantization (VQ) is discussed. This allows near-optimal performance in a mean square error sense while keeping the hardware complexity low. The encoder is partitioned into a slave processor chip that computes the distance and performs minimizations and an off-chip controller that directs the search. Pointer addressing is exploited in the codebook memory to keep the controller hardware simple. Inputs to the slave processor include the source vectors, the code vectors; and external control signals. The slave processor outputs the index of the code vector that best approximates the input in a mean square error sense. The layout for the slave processor has been generated using a 1.2- mu m CMOS library and measures 5.76*6.6 mm/sup 2/. Critical path simulation with SPICE indicates a throughput of 89 million multiply-accumulates per second. This implies that real-time processing at MPEG rates can be achieved if the number of levels (N7) and the number of children at any node (M) obey the constraint M*N >

Robust Audio-Codebooks for Large-Scale Event Detection in Consumer Videos

Abstract: In this paper we present our audio based system for detecting “events” within consumer videos (e.g. You Tube) and report our experiments on the TRECVID Multimedia Event Detection (MED) task and development data. Codebook or bag-of-words models have been widely used in text, visual and audio domains and form the state-of-the-art in MED tasks. The overall effectiveness of these models on such datasets depends critically on the choice of low-level features, clustering approach, sampling method, codebook size, weighting schemes and choice of classifier. In this work we empirically evaluate several approaches to model expressive and robust audio codebooks for the task of MED while ensuring compactness. First, we introduce the Large Scale Pooling Features (LSPF) and Stacked Cepstral Features for encoding local temporal information in audio codebooks. Second, we discuss several design decisions for generating and representing expressive audio codebooks and show how they scale to large datasets. Third, we apply text based techniques like Latent Dirichlet Allocation (LDA) to learn acoustictopics as a means of providing compact representation while maintaining performance. By aggregating these decisions into our model, we obtained 11% relative improvement over our baseline audio systems.

Image retrieval by Kekre's transform applied on each row of Walsh transformed VQ codebook

Abstract: The new technique for image retrieval using the color-texture features extracted from images based on vector quantization with Kekre's fast codebook generation is proposed. This gives better discrimination capability for CBIR. Here the database image is divided into 2x2 pixel windows to obtain 12 color descriptors per window (Red, Green and Blue per pixel) to form a vector. Collection of all such vectors is a training set. Then the Kekre's Fast Codebook Generation (KFCG) is applied on this set to get 16 codevectors. The Walsh transform is applied on each column of the codebook, followed by Kekre's transform applied on each row of the Walsh transformed codebook. This transform vector then is used as the image signature (feature vector) for image retrieval. The method takes lesser computations as compared to conventional Walsh applied on complete image. The method gives the color-texture features of the image database at reduced feature set size. Proposed method gives better precision and recall as compared to full Walsh based CBIR. Proposed method avoids resizing of images which is required for any transform based feature extraction method.

Quantization of input vectors with and without rearrangement of vector elements of a candidate vector

Abstract: For quantizing input vectors into output codes with reference to quantization vectors with reduction of a memory capacity, a vector quantizer device comprises a rearranging unit (21, 23) between a codebook circuit (17) preliminarily loaded, in accordance with codebook indexes, with code vectors selected from the quantization vectors to produce at least one candidate vector in response to a current index and a distance calculator (15) for calculating, between each input vector and comparison vectors given by the candidade vector, distance values for supply to an evaluation circuit (19) for producing a selected index indicative of one of the comparison vectors that minimizes the distance values and for successively producing the output codes with the selected index used as each output code without or with addition of a rearrangement index. When the rearrangement index is and is not added, the rearranging circuit produces the candidate vector in each comparison vector as an unchanged vector and as a rearranged vector in which vector elements of the candidate vector are rearranged, respectively. The rearranging unit may rearrange the candidate vector in compliance with a single predetermined rule or with rules preliminarily stored in a rearrangement table circuit (23) in accordance with table indexes with one of the rules delivered to a rearranging circuit (21) in response to the rearrangement index.

Multi-segment vector quantizer for a speech coder suitable for use in a radiotelephone

Abstract: A Vector-Sum Excited Linear Predictive Coding (VSELP) speech coder provides improved quality and reduced complexity over a typical speech coder. VSELP uses a codebook which has a predefined structure such that the computations required for the codebook search process can be significantly reduced. This VSELP speech coder uses single or multi-segment vector quantizer of the reflection coefficients based on a Fixed-Point-Lattice-Technique (FLAT). Additionally, this speech coder uses a pre-quantizer to reduce the vector codebook search complexity and a high-resolution scalar quantizer to reduce the amount of memory needed to store the reflection coefficient vector codebooks. Resulting in a high quality speech coder with reduced computations and storage requirements.