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HOW PHONETIC IS A PHONOLOGICAL feature REPRESENTATION - THE CASE OF LABIODENTAL FRICATIVES

SPEECH COMMUNICATION 1989年第4期8卷 329-345页

作者： BERG, T TECH UNIV BRAUNSCHWEIG DEPT ENGLISH LINGUIST MUEHLENPFORDTSTR 22-23 W-33 BRAUNSCHWEIG GERMANY

This paper examines the psychological reality of feature representations. Given the non-cognitive linguistic and the low-level phonetic approaches, it is a priori an open question whether the psycholinguistic representation borrows from both, from either or from neither of these. As a test case, a point of divergence between phoneticians and linguists has been selected for scrutiny. While the former consider [f] and [v] to be labiodental fricatives, the latter regard them as underlying bilabials or simply labials. To determine if [f] and [v] behave psycholinguistically like bilabial or labiodental segments, the interactions between the fricatives at issue and the other phonemes are analyzed in two large corpora of slips of the tongue in English and German. The results indicate that [f] and [v] are indistinguisable from bilabials, that is, they are as likely to substitute for other bilabials and as unlikely to replace non-bilabials in the way that [p], [m] or [w] do. Three hypotheses are put forward in an attempt to come to grips with this finding. According to the bilabialness-only and the labialness-only hypotheses there is no node for labiodentalness in the processing network. The rival account starts from the assumption that features are represented as vectors in a space coordinate system. In this concept, there is a vector for bilabialness as well as one for labiodentalness. It is claimed that these vectors are closer to each other than their actual phonetic distance would imply. There is less empirical support for the vector hypothesis than for the bilabialness-only one. It is concluded that phonetic and psycholinguistic feature representations need not match.

关键词： Concrete vs. abstract representations feature coding speech errors

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Moving scene object tracking method based on deep convolutional neural network

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ALEXANDRIA ENGINEERING JOURNAL 2024年 86卷 592-602页

作者： Liu, Long Lin, Bing Yang, Yong Chongqing Presch Educ Coll Sch Phys Educ Chongqing 404047 Peoples R China Zhengzhou Univ Sch Phys Educ Zhengzhou 450000 Peoples R China

The effect of target tracking is not ideal when facing various complex tracking scenarios such as non-rigid deformation of target, frequent occlusion, clutter of target background and interference of similar objects. In this paper, the feature based on deep convolutional neural network is used for target tracking in moving scenes, and a sliding window target segmentation method is proposed to study the impact of data normalization and data set expansion on the final result. In order to select more distinguishing features, principal component analysis is used to process the features of Deep Convolution Neural Network (DCNN), and the features of different network layers of DCNN are compared. The feature coding algorithm is studied, and the extracted DCNN features are encoded by Fisher Vectors algorithm, and compared with the locality-constrained linear encoding technique. Experiments show that the feature based on deep convolutional neural network in this paper can obtain higher accuracy than the traditional feature fusion method. According to the result analysis, the tracking accuracy of deep convolutional neural network algorithm is improved under the condition of illumination variation. In the case of local occlusion, the tracking accuracy is also improved.

关键词： Target tracking Motion scene Deep convolutional neural network feature coding

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Spatially Regularized and Locality-Constrained Linear coding for Human Action Recognition

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OPTICAL REVIEW 2014年第3期21卷 226-236页

作者： Wang, Bin Gai, Wen Guo, Shouchun Liu, Yu Wang, Wei Zhang, Maojun China Aerodynam Res & Dev Ctr Facil Design & Instrumentat Inst Mianyang 621000 Peoples R China Natl Univ Def Technol Coll Informat Syst & Management Changsha 410073 Hunan Peoples R China

To reduce quantization error, preserve the manifold of local features, distinguish the ambiguous features, and model the spatial configuration of features for Bag-of-features (BoF) model-based human action recognition, a novel feature coding method called spatially regularized and locality-constrained linear coding (SLLC) is proposed. The spatial regularization and locality constraint are involved in the feature coding phase to model the spatial configuration of features and preserve their nonlinear manifold. The action recognition experimental results on benchmark datasets show that SLLC achieves better performance than the state-of-the-art feature coding methods such as soft vector quantization, sparse coding, and locality-constrained linear coding. (C) 2014 The Japan Society of Applied Physics

关键词： image processing video context analysis action recognition Bag-of-features local spatiotemporal feature feature coding

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THE TEMPORAL RANGE OF MOTION SENSING AND MOTION PERCEPTION

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VISION RESEARCH 1990年第4期30卷 615-619页

作者： GEORGESON, MA HARRIS, MG UNIV BRISTOL DEPT PSYCHOL 8-10 BERKELEY SQ BRISTOL BS8 1HH AVON ENGLAND UNIV BIRMINGHAM DEPT PSYCHOL BIRMINGHAM B15 2TT W MIDLANDS ENGLAND

Apparent motion (AM) was studied using the missing-fundamental square-wave grating, displaced discretely over time. At inter-stimulus (ISIs) greater than about 40 msec, AM was seen in the direction of displacement of the visible features of the pattern, while at shorter ISIs AM was seen in the reversed direction, following the displacement of the third harmonic spatial frequency component. This confirms (a) that the "long-range", feature-based process can bridge much greater time-gaps than the "short-range" motion sensors and (b) that the missing-fundamental pattern is a particularly useful tool for teasing the two processes apart.

关键词： Apparent motion Gratings Missing fundamental feature coding

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Polish Text Steganography Method Using Letter Points and Extension 1

Polish Text Steganography Method Using Letter Points and Ext...

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IEEE International Conference on Electrical, Computer and Communication Technologies

作者： Khan, Sungkrityayan Abhijitha, B. Sankineni, Rishi Sunil, B. SRM Univ Dept Comp Sci & Engn Madras Tamil Nadu India

ISBN: (纸本)9781479960859

In this particular paper we have presented a new approach of steganography which is suitable for Polish texts. The approach can be assorted under feature coding methods of steganography. This approach involves the hiding of the information bits secretly within the letters gaining from their inherited points. To find out the specific letters holding the secret bits, the proposed method considers the two features, the extensions of the points in the letters and the redundant Polish extension character. The pointed letters with extension are used by us to hold the secret bit 'one' and the unpointed letters having an extension to hold the 'zero' bit. This particular steganography technique is found attractive to other languages having similar text to Polish such as Urdu, Persian, Hindi etc.

关键词： Polish text feature coding Text Steganography Cryptography Information Security Text watermarking

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Three Dimensional Palmprint Recognition

Three Dimensional Palmprint Recognition

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IEEE International Conference on Systems, Man and Cybernetics

作者： Li, Wei Zhang, Lei Zhang, David Shanghai Jiao Tong Univ Inst Image Proc & Pattern Recognit Shanghai 200030 Peoples R China Hong Kong Polytech Univ Biometr Res Ctr Dept Comp Hong Kong Peoples R China

ISBN: (纸本)9781424427932

Palmprint has been widely studied as its high accuracy and low cost. Most of the previous studies are based on two dimensional (2D) image of the palmprint. However, 2D image can be easily forged, which will threaten the security of palmprint authentication system. Furthermore, 2D image can be easily affected by noise, such as scrabbling and dirty in the palm. To overcome these shortcomings, we develop a three dimensional (3D) palmprint identification system. The structured-light imaging technology is adopted to collect the 3D palmprint data, from which the stable Mean Curvature Image (MCI) is extracted. Then the Competitive coding (CompCode) technique is used to code the 3D palmprint pattern according the MCI. By using score level fusion of MCI and its CompCode, promising recognition performance is achieved on our established 3D palmprint database.

关键词： 3D palmprint identification biometrics mean curvature feature coding

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DESCRIPTOR-BASED ADAPTIVE TRACKING-BY-DETECTION FOR VISUAL SENSOR NETWORKS

DESCRIPTOR-BASED ADAPTIVE TRACKING-BY-DETECTION FOR VISUAL S...

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IEEE International Conference on Multimedia & Expo Workshops (ICMEW)

作者： Panti, Berner Monteiro, Pedro Pereira, Fernando Ascenso, Joao Inst Super Tecn Inst Telecomunicacoes Lisbon Portugal

ISBN: (纸本)9781479970797

Local descriptors represent a powerful tool, which is exploited in several applications such as visual search, object recognition and visual tracking. Real-valued visual descriptors such as SIFT and SURF achieve state-of-the-art accuracy performance for a large set of visual analysis tasks. However, such algorithms are demanding in terms of computational capabilities and bandwidth, being unsuitable for scenarios where resources are constrained. In this context, binary descriptors provide an efficient alternative to real-valued descriptors, due to their low computational complexity, limited memory footprint and fast matching algorithms. In this paper, binary descriptors are used to perform visual tracking of an object along time. The proposed visual tracker performs descriptor matching between consecutive frames, applies filtering techniques to remove undesirable outliers and employs a suitable model to characterize the object appearance. In addition, techniques to code and transmit these description streams are employed, thus reducing the amount of data necessary to transmit to perform accurate object tracking. The efficiency of the proposed visual tracker is evaluated in terms of rate-accuracy, i.e. using the bitrate associated to the compressed binary descriptors and a quantitative metric to assess the accuracy of the visual tracker.

关键词： object tracking binary descriptors feature coding Hough transform tracking-by-detection

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Improving Security and Capacity for Arabic Text Steganography Using 'Kashida' Extensions

Improving Security and Capacity for Arabic Text Steganograph...

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7th ACS/IEEE International Conference on Computer Systems and Applications (AICCSA-09)

作者： Al-Haidari, Fahd Gutub, Adnan Al-Kahsah, Khalid Hamodi, Jameel King Fahd Univ Petr & Minerals Coll Comp Sci & Engn Dhahran 31261 Saudi Arabia

ISBN: (纸本)9781424438075

Steganography is a method of hiding data within a cover media so that other individuals fail to realize their existence. In this paper, a new approach for steganography in Arabic texts is proposed. The main idea is that each Arabic word may have some characters which can be extended by 'Kashida'. The ranks 'locations' of such characters and the inserted Kashida, construct a coding method to represent a block of secret bits. Different scenarios have been proposed based on the maximum number of Kashida possible to be inserted per word. The approach was compared to some existing Arabic text steganography approaches in terms of capacity and security. It is shown that this proposed approach outperforms the others with interesting promising results.

关键词： Arabic text Cryptography feature coding Information security Steganography Text watermarking

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SPATIAL PYRAMID ALIGNMENT FOR SPARSE coding BASED OBJECT CLASSIFICATION 24

SPATIAL PYRAMID ALIGNMENT FOR SPARSE CODING BASED OBJECT CLA...

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24th IEEE International Conference on Image Processing (ICIP)

作者： Kim, Joonsoo Tahboub, Khalid Delp, Edward J. Purdue Univ Sch Elect & Comp Engn Video & Image Proc Lab VIPER W Lafayette IN 47907 USA

ISBN: (纸本)9781509021758

The bag of visual words (BOW) model is widely used for image representation and classification. Spatial pyramid based feature pooling utilizes the BOW model and is the most popular approach to capture the spatial distribution (layout) of local image features, It makes the assumption that the center of an object is aligned with the center of an image, which can lead to misalignment and degradation in performance. In this paper, we propose a method to utilize max pooled features to estimate objects centers and align the spatial pyramid accordingly. We also propose an image representation descriptor robust to misalignments and objects deformations. The experimental results demonstrate that our spatial pyramid alignment method is simple yet efficient in handling misalignments and achieves high object classification accuracy.

关键词： object classification spatial pyramid feature coding spatial pyramid alignment

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coding MODE DECISION ALGORITHM FOR BINARY DESCRIPTOR coding 22

CODING MODE DECISION ALGORITHM FOR BINARY DESCRIPTOR CODING

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22nd European Signal Processing Conference (EUSIPCO)

作者： Monteiro, Pedro Ascenso, Joao Inst Telecomunicacoes Inst Super Tecn Lisbon Portugal

ISBN: (纸本)9780992862619

In visual sensor networks, local feature descriptors can be computed at the sensing nodes, which work collaboratively on the data obtained to make an efficient visual analysis. In fact, with a minimal amount of computational effort, the detection and extraction of local features, such as binary descriptors, can provide a reliable and compact image representation. In this paper, it is proposed to extract and code binary descriptors to meet the energy and bandwidth constraints at each sensing node. The major contribution is a binary descriptor coding technique that exploits the correlation using two different coding modes: Intra, which exploits the correlation between the elements that compose a descriptor;and Inter, which exploits the correlation between descriptors of the same image. The experimental results show bitrate savings up to 35% without any impact in the performance efficiency of the image retrieval task.

关键词： Local features feature coding binary descriptors mode decision visual sensor networks

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