• Title/Summary/Keyword: state recognition

Search Result 1,016, Processing Time 0.027 seconds

Gait Recognition Based on GF-CNN and Metric Learning

  • Wen, Junqin
    • Journal of Information Processing Systems
    • /
    • v.16 no.5
    • /
    • pp.1105-1112
    • /
    • 2020
  • Gait recognition, as a promising biometric, can be used in video-based surveillance and other security systems. However, due to the complexity of leg movement and the difference of external sampling conditions, gait recognition still faces many problems to be addressed. In this paper, an improved convolutional neural network (CNN) based on Gabor filter is therefore proposed to achieve gait recognition. Firstly, a gait feature extraction layer based on Gabor filter is inserted into the traditional CNNs, which is used to extract gait features from gait silhouette images. Then, in the process of gait classification, using the output of CNN as input, we utilize metric learning techniques to calculate distance between two gaits and achieve gait classification by k-nearest neighbors classifiers. Finally, several experiments are conducted on two open-accessed gait datasets and demonstrate that our method reaches state-of-the-art performances in terms of correct recognition rate on the OULP and CASIA-B datasets.

Concept and Construct of Problem Recognition Stage in Consumer Decision Making Process of Apparel Purchase (의복 구매 의사 결정 과정 중 문제인식 단계의 개념과 구조에 대한 연구)

  • 유연실;이은영
    • Journal of the Korean Society of Clothing and Textiles
    • /
    • v.22 no.6
    • /
    • pp.760-771
    • /
    • 1998
  • The purpose of this study is to clarify the concept and construct of the problem recognition stage in consumer decision making process of apparel Purchase. This study was supplemented by the theoretical study and field interviews. 40 women were interviewed on their apparel purchase situation to identify problem recognition process. As a result, the concept of problem recognition in apparel purchase is the perceived difference between the ideal state of apparel affairs and the actual situation sufficient to arouse and activate the decision making process. And the problem recognition stage in apparel purchase is constituted of the following steps: gestation, categorization, problem definition, and purchase intention formation. In most cases, these four steps existed, but in some cases several steps were deleted or condensed.

  • PDF

KMSAV: Korean multi-speaker spontaneous audiovisual dataset

  • Kiyoung Park;Changhan Oh;Sunghee Dong
    • ETRI Journal
    • /
    • v.46 no.1
    • /
    • pp.71-81
    • /
    • 2024
  • Recent advances in deep learning for speech and visual recognition have accelerated the development of multimodal speech recognition, yielding many innovative results. We introduce a Korean audiovisual speech recognition corpus. This dataset comprises approximately 150 h of manually transcribed and annotated audiovisual data supplemented with additional 2000 h of untranscribed videos collected from YouTube under the Creative Commons License. The dataset is intended to be freely accessible for unrestricted research purposes. Along with the corpus, we propose an open-source framework for automatic speech recognition (ASR) and audiovisual speech recognition (AVSR). We validate the effectiveness of the corpus with evaluations using state-of-the-art ASR and AVSR techniques, capitalizing on both pretrained models and fine-tuning processes. After fine-tuning, ASR and AVSR achieve character error rates of 11.1% and 18.9%, respectively. This error difference highlights the need for improvement in AVSR techniques. We expect that our corpus will be an instrumental resource to support improvements in AVSR.

Isolated Word Recognition Based on Finite-State Vector Quantization (유한상태 벡터양자화를 이용한 격리단어인식)

  • 윤원식;은종관
    • The Journal of the Acoustical Society of Korea
    • /
    • v.5 no.3
    • /
    • pp.50-57
    • /
    • 1986
  • 유한상태 벡터양자화 방법을 이용한 격리단어인식에 관하여 기술하고 있다. 이 인식시스템은 codebook과 next-state function 으로 구성된 일종의 finite-state machine으로 볼 수 있다. 유한상태 벡 터양자화방법을 이용한 격리단어 인식시스템은 일반적인 벡터양자화방법을 이용한 인식시스템에 비하여 소요시간이 감소하며 입력음성을 분할할 필요도 없는 한편 두 시스템의 인식율은 비슷한 것으로 나타났 다. Next-state function을 구하는 방법에는 conditional histogram 방법과 omniscient design 방법이 있 으며, 이 방법들의 성능비교를 위해 영부터 구까지의 한국어 숫자음성에 대한 인식실험을 수행하였다.

  • PDF

Isolated-Word Recognition Using Neural Network and Hidden Markov Model (Neural-HMM을 이용한 고립단어 인식)

  • 김연수;김창석
    • The Journal of Korean Institute of Communications and Information Sciences
    • /
    • v.17 no.11
    • /
    • pp.1199-1205
    • /
    • 1992
  • In this paper, a Korean word recognition method which usese Neural Network and Hidden Markov Models(HMM) is proposed to improve a recognition rate with a small amount of learning data. The method reduces the fluctuation due to personal differences which is a problem to a HMM recognition system. In this method, effective recognizer is designed by the complement of each recognition result of the Hidden Markov Models(HMM) and Neural Network. In order to evaluate this model, word recognition experiment is carried out for 28 cities which is DDD area names uttered by two male and a female in twenties. As a result of testing HMM with 8 state, codeword is 64, the recognition rate 91[%], as a result of testing Neural network(NN) with 64 codeword the recognition rate is 89[%]. Finally, as a result of testing NN-HMM with 64 codeword which the best condition in former tests, the recognition rate is 95[%].

  • PDF

Boosting the Face Recognition Performance of Ensemble Based LDA for Pose, Non-uniform Illuminations, and Low-Resolution Images

  • Haq, Mahmood Ul;Shahzad, Aamir;Mahmood, Zahid;Shah, Ayaz Ali;Muhammad, Nazeer;Akram, Tallha
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • v.13 no.6
    • /
    • pp.3144-3164
    • /
    • 2019
  • Face recognition systems have several potential applications, such as security and biometric access control. Ongoing research is focused to develop a robust face recognition algorithm that can mimic the human vision system. Face pose, non-uniform illuminations, and low-resolution are main factors that influence the performance of face recognition algorithms. This paper proposes a novel method to handle the aforementioned aspects. Proposed face recognition algorithm initially uses 68 points to locate a face in the input image and later partially uses the PCA to extract mean image. Meanwhile, the AdaBoost and the LDA are used to extract face features. In final stage, classic nearest centre classifier is used for face classification. Proposed method outperforms recent state-of-the-art face recognition algorithms by producing high recognition rate and yields much lower error rate for a very challenging situation, such as when only frontal ($0^{\circ}$) face sample is available in gallery and seven poses ($0^{\circ}$, ${\pm}30^{\circ}$, ${\pm}35^{\circ}$, and ${\pm}45^{\circ}$) as a probe on the LFW and the CMU Multi-PIE databases.

Relationship between the State of Decision Making Recognition Technology for Daily Living and Activities of Daily Living(ADL) of Inpatients in Geriatric Hospital on the Patient Core Card (환자평가표에 의한 요양병원 입원 노인들의 일상생활사 의사결정 인식기술 상태와 일상생활수행능력 간의 관계)

  • Lim, Jung-Do;Lee, Sung-Ho
    • The Journal of the Korea Contents Association
    • /
    • v.14 no.11
    • /
    • pp.328-336
    • /
    • 2014
  • This work has performed to find what activities of daily living are required for the intensive interests when inpatient elderly more than 3 months has been supported and convalescent care, where the inpatient elderly were judged by the inpatient assessment report in the time of December, 2013. According to the estimation with logistic function of the relationship between the state of decision making recognition technology and the Activities of Daily Living(ADL), the intensive cares for the elderly are required in the parameters of 'Having meal' and 'transferring sitting' when they are severed and convalescently cared as the degree of functional independence for ADL are severly proceeded. In addition, the senescence and disease the activities except 'Having meal' and 'transferring sitting' seem to be influenced by the decline of body function more than the state of decision making recognition technology for daily living.

An Improved Grammatical Structure of the FSN for the Recognition of Korean Price Sentences (한국어 가격 문장인식을 위한 FSN의 개선된 문법적 구조)

  • 김동주;홍광석
    • Journal of the Institute of Convergence Signal Processing
    • /
    • v.3 no.3
    • /
    • pp.1-5
    • /
    • 2002
  • In this paper, we present an improved grammatical structure of the finite state network(FSN) for constructing useful recognizer of practical Korean price sentences. The grammar constraints of Korean price sentences in the existing method are necessary to modify grammar constraint and grammatical structure for the recognition of practical Korean price sentences. The grammar constraints are improved in the third and the fourth grammar constraint of Korean price sentences for the practical point. In this paper, we improve the grammar constraints and make up for the weak point in the grammatical structure of the FSN[1]. Three kinds of experiments were performed to evaluate the improved grammatical structures; FSN0, FSN-1, FSN-2. As the recognition results for price sentences, the word recognition rates were 81.37%, 83.92%, and 85.49%, for FSN0, FSN-1, and FSN-2. Also, the sentence recognition rates were 35%, 45%, and 52%, respectively.

  • PDF

Efficient context dependent process modeling using state tying and decision tree-based method (상태 공유와 결정트리 방법을 이용한 효율적인 문맥 종속 프로세스 모델링)

  • Ahn, Chan-Shik;Oh, Sang-Yeob
    • Journal of Korea Multimedia Society
    • /
    • v.13 no.3
    • /
    • pp.369-377
    • /
    • 2010
  • In vocabulary recognition systems based on HMM(Hidden Markov Model)s, training process unseen model bring on show a low recognition rate. If recognition vocabulary modify and make an addition then recreated modeling of executed database collected and training sequence on account of bring on additional expenses and take more time. This study suggest efficient context dependent process modeling method using decision tree-based state tying. On study suggest method is reduce recreated of model and it's offered that robustness and accuracy of context dependent acoustic modeling. Also reduce amount of model and offered training process unseen model as concerns context dependent a likely phoneme model has been used unseen model solve the matter. System performance as a result of represent vocabulary dependence recognition rate of 98.01%, vocabulary independence recognition rate of 97.38%.

Automatic Recognition of the Front/Back Sides and Stalk States for Mushrooms(Lentinus Edodes L.) (버섯 전후면과 꼭지부 상태의 자동 인식)

  • Hwang, H.;Lee, C.H.
    • Journal of Biosystems Engineering
    • /
    • v.19 no.2
    • /
    • pp.124-137
    • /
    • 1994
  • Visual features of a mushroom(Lentinus Edodes, L.) are critical in grading and sorting as most agricultural products are. Because of its complex and various visual features, grading and sorting of mushrooms have been done manually by the human expert. To realize the automatic handling and grading of mushrooms in real time, the computer vision system should be utilized and the efficient and robust processing of the camera captured visual information be provided. Since visual features of a mushroom are distributed over the front and back sides, recognizing sides and states of the stalk including the stalk orientation from the captured image is a prime process in the automatic task processing. In this paper, the efficient and robust recognition process identifying the front and back side and the state of the stalk was developed and its performance was compared with other recognition trials. First, recognition was tried based on the rule set up with some experimental heuristics using the quantitative features such as geometry and texture extracted from the segmented mushroom image. And the neural net based learning recognition was done without extracting quantitative features. For network inputs the segmented binary image obtained from the combined type automatic thresholding was tested first. And then the gray valued raw camera image was directly utilized. The state of the stalk seriously affects the measured size of the mushroom cap. When its effect is serious, the stalk should be excluded in mushroom cap sizing. In this paper, the stalk removal process followed by the boundary regeneration of the cap image was also presented. The neural net based gray valued raw image processing showed the successful results for our recognition task. The developed technology through this research may open the new way of the quality inspection and sorting especially for the agricultural products whose visual features are fuzzy and not uniquely defined.

  • PDF