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Adaptable Similarity Search Using Vector Quantization
[chapter]
2001
Lecture Notes in Computer Science
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Adaptable similarity queries based on quadratic form distance functions are widely popular in data mining applications, particularly for domains such as multimedia, CAD, molecular biology or medical image ...
In this paper, we address the problem that determining quadratic form distances between quantized vectors is difficult and computationally expensive. ...
. for all : Vector Quantization. ...
doi:10.1007/3-540-44801-2_31
fatcat:jcgrx26ymbgv7luvxtc4vzxwxq
An Efficient Coding Method for Teleconferencing Video and Confocal Microscopic Image Sequences
2008
Journal of Computing and Information Technology
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The adaptive vector quantization algorithm is used to train the codebook for optimal performance with time. ...
The algorithm uses a 3D vector quantization pyramidal codebook-based model with adaptive pyramidal codebook for compression. ...
The vector quantization and adaptive codebook procedures are explained in Section 2. 3D vector quantization used for compression and encoding of teleconferencing videos and confocal microscopic image sequences ...
doi:10.2498/cit.1000892
fatcat:wsknuacp4bfbll6igui5flhpze
Motion Estimation For High Performance Transcoding
1998
International Conference on Consumer Electronics
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With a highly reduced computational complexity, the proposed adaptive motion vector refinement achieves significant quality improvement in comparison to the conventional motion vector re-use scheme. ...
To improve the video quality, we proposed an adaptive motion vector refinement. ...
In comparison, the proposed adaptive motion vector refinement is similar in performance to the motion vector refinement. ...
doi:10.1109/icce.1998.678286
fatcat:vntzf7hbhnebne3lmh6bvtw4qu
Motion estimation for high performance transcoding
1998
IEEE transactions on consumer electronics
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With a highly reduced computational complexity, the proposed adaptive motion vector refinement achieves significant quality improvement in comparison to the conventional motion vector re-use scheme. ...
To improve the video quality, we proposed an adaptive motion vector refinement. ...
In comparison, the proposed adaptive motion vector refinement is similar in performance to the motion vector refinement. ...
doi:10.1109/30.713176
fatcat:ht4rskcjxrck7klccifeoskxn4
Adaptive Difference Compensation Vector Quantization Using Dynamic Image Block Adjustment
2016
International Journal of Hybrid Information Technology
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A method for image compression, adaptive difference compensation vector quantization using dynamic image block adjustment is proposed in this paper. ...
The experiment results reveal that this proposed method can improve the encoding speed and image restoration performance against the normal vector quantization. ...
., [6] presented a novel multiresolution, perceptual and vector quantization based video coding scheme and the detail subbands are vector quantized using an adaptive vector quantization scheme. ...
doi:10.14257/ijhit.2016.9.3.36
fatcat:faxvgu34wbbwjpegedfyqxrpby
Spreading vectors for similarity search
[article]
2019
arXiv
pre-print
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State-of-the-art techniques learn parameters of quantizers on training data for optimal performance, thus adapting quantizers to the data. ...
In this work, we propose to reverse this paradigm and adapt the data to the quantizer: we train a neural net which last layer forms a fixed parameter-free quantizer, such as pre-defined points of a hyper-sphere ...
SIMILARITY SEARCH WITH LATTICE VECTOR QUANTIZERS We evaluate the lattice-based indexing proposed in Section 4, and compare it to more conventional methods based on quantization, namely PQ (Jégou et al ...
arXiv:1806.03198v3
fatcat:glvg7h5jqbfxdasbn5r4pxokqi
Motion vector refinement for high-performance transcoding
1999
IEEE transactions on multimedia
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We propose a fast-search adaptive motion vector refinement scheme that is capable of providing video quality comparable to that can be achieved by performing a new full-scale motion estimation but with ...
The composed motion vector can also be refined using the proposed motion vector refinement scheme to achieve better results. ...
The vertical search is performed in a similar way. Fig. 12 (a) shows the best case for a search range of 2 pixels. ...
doi:10.1109/6046.748169
fatcat:mgea6rr7r5gsfmcpycjcvp3s3a
4.-8. März 2019
2019
Datenbanksysteme für Business, Technologie und Web
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The benefits of operations on dense vectors like word embeddings for analytical functionalities of RDBMSs motivate an integration of kNN-Joins. ...
K nearest neighbor search (kNN-Search) is a universal data processing technique and a fundamental operation for word embeddings trained by word2vec or related approaches. ...
An integration of vector similarity search for high dimensional data into Spark has been done by [BBS17] for word embeddings. ...
doi:10.18420/btw2019-15
dblp:conf/btw/GuntherTL19
fatcat:kjdfuowc5bagtgggrkyo2g34i4
Deep Visual-Semantic Quantization for Efficient Image Retrieval
2017
2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
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The main contribution lies in jointly learning deep visual-semantic embeddings and visual-semantic quantizers using carefullydesigned hybrid networks and well-specified loss functions. ...
has already shown the superior performance over the hashing solutions for similarity retrieval. ...
Approximate nearest neighbor (ANN) search by maximum inner-product similarity is a powerful tool in quantization methods [11] . ...
doi:10.1109/cvpr.2017.104
dblp:conf/cvpr/CaoL0L17
fatcat:jgzhlmcoeraqblejcdeoeovh6i
Adaptive Cluster-Distance Bounding for Nearest Neighbor Search in Image Databases
2007
2007 IEEE International Conference on Image Processing
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We consider approaches for exact similarity search in a high dimensional space of correlated features representing image datasets, based on principles of clustering and vector quantization. ...
We develop an adaptive cluster distance bound based on separating hyperplanes, that complements our index in selectively retrieving clusters that contain data entries closest to the query. ...
Similarity search is the search for elements in the database most similar to the query image. ...
doi:10.1109/icip.2007.4379601
dblp:conf/icip/RamaswamyR07
fatcat:ne7teonnlzgjna6c5vh7t4msyi
Interactive Exploration for Image Retrieval
2005
EURASIP Journal on Advances in Signal Processing
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It is based on adaptive quantization of the color space, together with new features aiming at representing the spatial relationship between colors. Color analysis is also extended to texture. ...
Using these powerful indexes, an original interactive retrieval strategy is introduced. The process is based on two steps for handling the retrieval of very large image categories. ...
The adaptation then consists in moving the query vector, or in changing similarity parameters. Sometimes both are combined [12] . ...
doi:10.1155/asp.2005.2173
fatcat:hb47phaysve3bb6evqfxlzbvnu
A fast full-search adaptive vector quantizer for video coding
2001
Conference Record of Thirty-Fifth Asilomar Conference on Signals, Systems and Computers (Cat.No.01CH37256)
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It uses an adaptive-search, variable-length encoding method which allows for very fast matching of a wide range of transmission rates. ...
Simulations show that full-search tree residual VQ (FTRVQ) can provide up to 3 dB improvement over a similar RVQ encoder on video sequences. ...
A VIDEO CODING ALGORITHM USING RATE-DISTORTION ADAPTIVE-SEARCH METHODS Simulations on video sequences were performed with an adaptive-search, locally rate-distortion optimal, mean-removed quantizer described ...
doi:10.1109/acssc.2001.986943
fatcat:g7iladzn2rax5nk2vtqkvjomw4
Hybrid low bitrate audio coding using adaptive gain shape vector quantization
2008
2008 IEEE 10th Workshop on Multimedia Signal Processing
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The other portions (typically the higher portions) of the spectrum are coded at a low bitrate using an adaptive gain shape vector quantizer where the codebook for vector quantization is formed by unmodified ...
In this paper we present a novel scheme to code audio signals at low bitrates which uses a traditional scalar quantization followed by entropy coding to code some portions of the spectrum (typically the ...
of the spectrum using adaptive vector quantization. ...
doi:10.1109/mmsp.2008.4665207
dblp:conf/mmsp/MehrotraCKT08
fatcat:kroa2twbdjfjtm44appdsqzori
Efficient and portable content-based music retrieval system
2014
2014 International Conference on Orange Technologies
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By using the vector quantization, we can achieve the high accuracy in audio retrieval rate. ...
In the proposed CBMR system, the use of 128 clusters in Kmeans-clustering quantization algorithm can achieve 87% retrieval accuracy and 90% high retrieval accuracy rate with the tree-based quantization ...
Next, a quantizer is constructed using the quantization methods based on the feature vectors. This quantizer transforms the feature vectors of training data into histograms. ...
doi:10.1109/icot.2014.6956622
fatcat:rbnb5g4piraorgcuhkv6vvfiva
Approximate search with quantized sparse representations
[article]
2016
arXiv
pre-print
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This paper tackles the task of storing a large collection of vectors, such as visual descriptors, and of searching in it. ...
As opposed to traditional sparse coding methods, quantized sparse coding includes memory usage as a design constraint, thereby allowing us to index a large collection such as the BIGANN billion-sized benchmark ...
This classic vector quantization approach was recently used for approximate search [1, 8, 24] . ...
arXiv:1608.03308v1
fatcat:5ovfqxfr7bfsng56x6vf4v4z3m
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