• Title/Summary/Keyword: Feature representation

Search Result 422, Processing Time 0.029 seconds

Face Recognition Robust to Local Distortion Using Modified ICA Basis Image

  • Kim Jong-Sun;Yi June-Ho
    • Proceedings of the Korea Institutes of Information Security and Cryptology Conference
    • /
    • 2006.06a
    • /
    • pp.251-257
    • /
    • 2006
  • The performance of face recognition methods using subspace projection is directly related to the characteristics of their basis images, especially in the cases of local distortion or partial occlusion. In order for a subspace projection method to be robust to local distortion and partial occlusion, the basis images generated by the method should exhibit a part-based local representation. We propose an effective part-based local representation method named locally salient ICA (LS-ICA) method for face recognition that is robust to local distortion and partial occlusion. The LS-ICA method only employs locally salient information from important facial parts in order to maximize the benefit of applying the idea of 'recognition by parts.' It creates part-based local basis images by imposing additional localization constraint in the process of computing ICA architecture I basis images. We have contrasted the LS-ICA method with other part-based representations such as LNMF (Localized Non-negative Matrix Factorization)and LFA (Local Feature Analysis). Experimental results show that the LS-ICA method performs better than PCA, ICA architecture I, ICA architecture II, LFA, and LNMF methods, especially in the cases of partial occlusions and local distortion

  • PDF

Semantic Aspects of Negation as Schema (부정 스키마의 의미론적 양상)

  • Tae, Kang-Soo
    • The KIPS Transactions:PartB
    • /
    • v.9B no.1
    • /
    • pp.23-28
    • /
    • 2002
  • A fundamental problem in building an intelligent agent is that an agent does not understand the meaning of its perception or its action. One reason that an agent cannot understand the world is partially caused by a syntactic approach that converts a semantic feature into a simple string. To solve this problem, Cohen introduces a semantic approach that an agent autonomously learns a meaningful representation of physical schemas, on which some advanced conceptual structures are built, from physically interacting with environment using its own sensors and effectors. However, Cohen does not deal with a meta level of conceptual primitive that makes recognizing a schema possible. We propose that negation is a meta schema that enables an agent to recognize a physical schema. We prove some semantic aspects of negation.

Similarity Assessment for Geometric Query on Mechanical Parts (기계부품의 형상검색은 위한 유사성 평가방법)

  • 김철영;김영호;강석호
    • Korean Journal of Computational Design and Engineering
    • /
    • v.5 no.2
    • /
    • pp.103-112
    • /
    • 2000
  • CAD databases are the core element to the management of product information. A key to the successful use of the databases is a rational method of query to and retrieval from the databases. Although it is parts geometry that users eager to retrieve from the CAD databases, no system yet supports geometry-based query. This paper aims at developing a new method of assessing geometric similarity which can serve as the basis of geometric query for CAD database. The proposed method uses ASVP (Alternating Sums of Volumes with Partitioning) decomposition that is a volumetric representation of a part obtained from its boundary representation. A measure of geometric similarity between two solid models is defined on their ASVP tree representations. The measure can take into account overall shapes of parte, shapes of features and their locations. Several properties that a similarity measure needs to satisfy are discussed. The geometric query developed in this paper can be used in a wide range of applications using CAD databases, which include similarity-based design retrieval, variant process planning, and components selection from part library. An experiment has been carried out to demonstrate the effectiveness of the method, and the results are presented.

  • PDF

Face Recognition using Non-negative Matrix Factorization and Learning Vector Quantization (비음수 행렬 분해와 학습 벡터 양자화를 이용한 얼굴 인식)

  • Jin, Donghan;Kang, Hyunchul
    • Journal of the Institute of Electronics and Information Engineers
    • /
    • v.54 no.3
    • /
    • pp.55-62
    • /
    • 2017
  • Non-negative matrix factorization (NMF) is one of the typical parts-based representation in which images are expressed as a linear combination of basis vectors that show the lcoal features or objects in the images. In this paper, we represent face images using various NMF methods and recognize their face identities based on extracted features using a learning vector quantization. We analyzed the various NMF methods by comparing extracted basis vectors. Also we confirmed the availability of NMF to the face recognition by verification of recognition rate of the various NMF methods.

Creative Method of Post-modernism Expressed in Modern Fashion (현대패션에 표현된 포스트모더니즘의 창조방법)

  • Lee, Eun-Kyung
    • Korean Journal of Human Ecology
    • /
    • v.11 no.3
    • /
    • pp.287-299
    • /
    • 2002
  • Post-modernism exists with different shapes in overall cultural phenomena. Among the creative methods of composing post-modernism, there are representation, parody, plural coding, trans avant-garde etc. Summing up the influence of creative method of post-modernism on modem fashion led to the following results. 1. The phenomenon appears that value and valuelessness are easily reversed, and things with historical and traditional meanings are being ignored. 2. The boundary between higher culture and public culture is being disorganized, and mixed imitation phenomenon ignoring the differences between male and female is emerging 3. The mental and historial aspects in fashion pattern are highly thought of and the trend to understand human body from the various angles emerges. 4. In the consumer-oriented society, it appears in the form of meanings to achieve the self-achievement in individual life, to express one's idea and desire in the esthetical point of views. 5. It shows that through arranging the striking things and the distorted things, it takes the compromised method of re-appreciating the existing ideas. The phenomena in the post-modernism occurring in fashion design forced the concept of the uniformed existing fashion to be changed, creating a various fashions. That can just be called the dehumanization trend in the era of post-modernism, which is the most important formative feature in modern fashion.

  • PDF

Prosodic Annotation in a Thai Text-to-speech System

  • Potisuk, Siripong
    • Proceedings of the Korean Society for Language and Information Conference
    • /
    • 2007.11a
    • /
    • pp.405-414
    • /
    • 2007
  • This paper describes a preliminary work on prosody modeling aspect of a text-to-speech system for Thai. Specifically, the model is designed to predict symbolic markers from text (i.e., prosodic phrase boundaries, accent, and intonation boundaries), and then using these markers to generate pitch, intensity, and durational patterns for the synthesis module of the system. In this paper, a novel method for annotating the prosodic structure of Thai sentences based on dependency representation of syntax is presented. The goal of the annotation process is to predict from text the rhythm of the input sentence when spoken according to its intended meaning. The encoding of the prosodic structure is established by minimizing speech disrhythmy while maintaining the congruency with syntax. That is, each word in the sentence is assigned a prosodic feature called strength dynamic which is based on the dependency representation of syntax. The strength dynamics assigned are then used to obtain rhythmic groupings in terms of a phonological unit called foot. Finally, the foot structure is used to predict the durational pattern of the input sentence. The aforementioned process has been tested on a set of ambiguous sentences, which represents various structural ambiguities involving five types of compounds in Thai.

  • PDF

A Representation and Matching Method for Shape-based Leaf Image Retrieval (모양기반 식물 잎 이미지 검색을 위한 표현 및 매칭 기법)

  • Nam, Yun-Young;Hwang, Een-Jun
    • Journal of KIISE:Software and Applications
    • /
    • v.32 no.11
    • /
    • pp.1013-1020
    • /
    • 2005
  • This paper presents an effective and robust leaf image retrieval system based on shape feature. Specifically, we propose an improved MPP algorithm for more effective representation of leaf images and show a new dynamic matching algorithm that basically revises the Nearest Neighbor search to reduce the matching time. In particular, both leaf shape and leaf arrangement can be sketched in the query for better accuracy and efficiency. In the experiment, we compare our proposed method with other methods including Centroid Contour Distance(CCD), Fourier Descriptor, Curvature Scale Space Descriptor(CSSD), Moment Invariants, and MPP. Experimental results on one thousand leaf images show that our approach achieves a better performance than other methods.

Modulation Recognition of BPSK/QPSK Signals based on Features in the Graph Domain

  • Yang, Li;Hu, Guobing;Xu, Xiaoyang;Zhao, Pinjiao
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • v.16 no.11
    • /
    • pp.3761-3779
    • /
    • 2022
  • The performance of existing recognition algorithms for binary phase shift keying (BPSK) and quadrature phase shift keying (QPSK) signals degrade under conditions of low signal-to-noise ratios (SNR). Hence, a novel recognition algorithm based on features in the graph domain is proposed in this study. First, the power spectrum of the squared candidate signal is truncated by a rectangular window. Thereafter, the graph representation of the truncated spectrum is obtained via normalization, quantization, and edge construction. Based on the analysis of the connectivity difference of the graphs under different hypotheses, the sum of degree (SD) of the graphs is utilized as a discriminate feature to classify BPSK and QPSK signals. Moreover, we prove that the SD is a Schur-concave function with respect to the probability vector of the vertices (PVV). Extensive simulations confirm the effectiveness of the proposed algorithm, and its superiority to the listed model-driven-based (MDB) algorithms in terms of recognition performance under low SNRs and computational complexity. As it is confirmed that the proposed method reduces the computational complexity of existing graph-based algorithms, it can be applied in modulation recognition of radar or communication signals in real-time processing, and does not require any prior knowledge about the training sets, channel coefficients, or noise power.

3D Cross-Modal Retrieval Using Noisy Center Loss and SimSiam for Small Batch Training

  • Yeon-Seung Choo;Boeun Kim;Hyun-Sik Kim;Yong-Suk Park
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • v.18 no.3
    • /
    • pp.670-684
    • /
    • 2024
  • 3D Cross-Modal Retrieval (3DCMR) is a task that retrieves 3D objects regardless of modalities, such as images, meshes, and point clouds. One of the most prominent methods used for 3DCMR is the Cross-Modal Center Loss Function (CLF) which applies the conventional center loss strategy for 3D cross-modal search and retrieval. Since CLF is based on center loss, the center features in CLF are also susceptible to subtle changes in hyperparameters and external inferences. For instance, performance degradation is observed when the batch size is too small. Furthermore, the Mean Squared Error (MSE) used in CLF is unable to adapt to changes in batch size and is vulnerable to data variations that occur during actual inference due to the use of simple Euclidean distance between multi-modal features. To address the problems that arise from small batch training, we propose a Noisy Center Loss (NCL) method to estimate the optimal center features. In addition, we apply the simple Siamese representation learning method (SimSiam) during optimal center feature estimation to compare projected features, making the proposed method robust to changes in batch size and variations in data. As a result, the proposed approach demonstrates improved performance in ModelNet40 dataset compared to the conventional methods.

Dynamic Hand Gesture Recognition Using CNN Model and FMM Neural Networks (CNN 모델과 FMM 신경망을 이용한 동적 수신호 인식 기법)

  • Kim, Ho-Joon
    • Journal of Intelligence and Information Systems
    • /
    • v.16 no.2
    • /
    • pp.95-108
    • /
    • 2010
  • In this paper, we present a hybrid neural network model for dynamic hand gesture recognition. The model consists of two modules, feature extraction module and pattern classification module. We first propose a modified CNN(convolutional Neural Network) a pattern recognition model for the feature extraction module. Then we introduce a weighted fuzzy min-max(WFMM) neural network for the pattern classification module. The data representation proposed in this research is a spatiotemporal template which is based on the motion information of the target object. To minimize the influence caused by the spatial and temporal variation of the feature points, we extend the receptive field of the CNN model to a three-dimensional structure. We discuss the learning capability of the WFMM neural networks in which the weight concept is added to represent the frequency factor in training pattern set. The model can overcome the performance degradation which may be caused by the hyperbox contraction process of conventional FMM neural networks. From the experimental results of human action recognition and dynamic hand gesture recognition for remote-control electric home appliances, the validity of the proposed models is discussed.