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CodePhys: Robust Video-Based Remote Physiological Measurement Through Latent Codebook Querying

IEEE Journal of Biomedical and Health Informatics 2025年 PP卷 PP页

作者： Chu, Shuyang Xia, Menghan Yuan, Mengyao Liu, Xin Seppanen, Tapio Zhao, Guoying Shi, Jingang Xi'an Jiaotong University School of Software Engineering Xi'an China Tencent Ai Lab Shenzhen China Lappeenranta-Lahti University of Technology Lut Computer Vision and Pattern Recognition Laboratory Lappeenranta53850 Finland University of Oulu Center for Machine Vision and Signal Analysis Finland

Remote photoplethysmography (rPPG) aims to measure non-contact physiological signals from facial videos, which has shown great potential in many applications. Most existing methods directly extract video-based rPPG features by designing neural networks for heart rate estimation. Although they can achieve acceptable results, the recovery of rPPG signal faces intractable challenges when interference from real-world scenarios takes place on facial video. Specifically, facial videos are inevitably affected by non-physiological factors (e.g., camera device noise, defocus, and motion blur), leading to the distortion of extracted rPPG signals. Recent rPPG extraction methods are easily affected by interference and degradation, resulting in noisy rPPG signals. In this paper, we propose a novel method named CodePhys, which innovatively treats rPPG measurement as a code query task in a noise-free proxy space (i.e., codebook) constructed by ground-truth PPG signals. We consider noisy rPPG features as queries and generate high-fidelity rPPG features by matching them with noise-free PPG features from the codebook. Our approach also incorporates a spatial-aware encoder network with a spatial attention mechanism to highlight physiologically active areas and uses a distillation loss to reduce the influence of non-periodic visual interference. Experimental results on four benchmark datasets demonstrate that CodePhys outperforms state-of-the-art methods in both intra-dataset and cross-dataset settings. © 2025 IEEE.

关键词： Heart

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CodePhys: Robust Video-based Remote Physiological Measurement through Latent Codebook Querying

arXiv

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arXiv 2025年

作者： Chu, Shuyang Xia, Menghan Yuan, Mengyao Liu, Xin Seppanen, Tapio Zhao, Guoying Shi, Jingang The School of Software Engineering Xi’an Jiaotong University Xi’an China The Tencent AI Lab Shenzhen China The Computer Vision and Pattern Recognition Laboratory Lappeenranta-Lahti University of Technology LUT Lappeenranta53850 Finland The Center for Machine Vision and Signal Analysis University of Oulu Finland

关键词： Heart

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A Holistic Approach for recognition of Complete Urdu Ligatures Using Hidden Markov Models

A Holistic Approach for Recognition of Complete Urdu Ligatur...

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Frontiers of Information Technology (FIT)

作者： Israr Uddin Imran Siddiqi Shehzad Khalid Center of Computer Vision and Pattern Recognition Bahria University Islamabad Pakistan

Optical Character recognition (OCR) is one of the continuously explored problems. Presently, commercial character recognizers are available reporting near to 100% recognition rates on text in a number of scripts. Despite these advancements, OCR systems however, have yet to mature for cursive scripts like Urdu. This study presents a holistic technique for recognition of Urdu text in Nastaliq font using "complete" ligatures as recognition units. The term "complete" refers to a partial word including its main body and secondary components (dots and diacritic marks). Discrete Wavelet Transform (DWT) is employed as feature extractor while a separate Hidden Markov Model (HMM) is trained for each ligature considered in our study. More than 2000 frequently used unique Urdu ligatures from the standard CLE (center of Language Engineering) dataset are considered in our evaluations. The system reads a promising accuracy of 88.87% on more than 10,000 partial words.

关键词： Character recognition Feature extraction Hidden Markov models Text recognition Discrete wavelet transforms Training Optical character recognition software

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Using electromagnetic input for multi-user or two-handed spatial gestural interaction based on the digital compass 15

Using electromagnetic input for multi-user or two-handed spa...

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17th International Conference on Human-computer Interaction with Mobile Devices and Services, MobileHCI 2015

作者： Yuksel, Kamer Ali Baz, Ipek Ozduman, Haluk Computer Vision and Pattern Recognition Laboratory Sabanci University Turkey Research Center for ICT German Turkish Advanced Technical University of Berlin Germany

ISBN: (纸本)9781450336529

Multiple researchers recently proposed the use of the digital compass embedded in mobile devices for touchless interaction in the 3D space around them. These methods overcome several limits imposed by other interaction techniques and were evaluated for a variety of uses. However, they do not support collaborative settings and are prone to dynamic noise caused by external conditions, as with most other sensor-based interaction techniques. In this paper, we propose the use of frequency-modulated electromagnets as an input medium for magnetic interaction to overcome its various constraints and further enable multi-user and two-handed input. Furthermore, we demonstrated the hardware design specifications of a novel input device, referred to as electromagnetic stylus, which is prototyped to conduct a user-study on the proposed method. Experimental results indicate that gestures performed simultaneously by four electromagnetic styli can accurately be recognized using a single magnetic field sensor, and dynamic noises can be substantially reduced. © 2015 ACM.

关键词： Timing circuits

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A new method for handwritten scene text detection in video

A new method for handwritten scene text detection in video

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International Conference on Frontiers in Handwriting recognition

作者： Shivakumara, Palaiahnakote Dutta, Anjan Pal, Umapada Tan, Chew Lim School of Computing National University of Singapore Singapore Singapore Computer Vision Center Universitat Autònoma de Barcelona Barcelona Spain Computer Vision and Pattern Recognition Unit Indian Statistical Institute India

ISBN: (纸本)9780769542218

There are many video images where hand written text may appear. Therefore handwritten scene text detection in video is essential and useful for many applications for efficient indexing, retrieval etc. Also there are many video frames where text line may be multi-oriented in nature. To the best of our knowledge there is no work on handwritten text detection in video, which is multi-oriented in nature. In this paper, we present a new method based on maximum color difference and boundary growing method for detection of multi-oriented handwritten scene text in video. The method computes maximum color difference for the average of R, G and B channels of the original frame to enhance the text information. The output of maximum color difference is fed to a K-means algorithm with K=2 to separate text and non-text clusters. Text candidates are obtained by intersecting the text cluster with the Sobel output of the original frame. To tackle the fundamental problem of different orientations and skews of handwritten text, boundary growing method based on a nearest neighbor concept is employed. We evaluate the proposed method by testing on our own handwritten text database and publicly available video data (Hua's data). Experimental results obtained from the proposed method are promising. © 2010 IEEE.

关键词： Color

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Sketch-based Facial Expression recognition for Human Figure Drawing Psychological Test

Sketch-based Facial Expression Recognition for Human Figure ...

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Frontiers of Information Technology (FIT)

作者： Momina Moetesum Tasneem Aslam Hassan Saeed Imran Siddiqi Uzma Masroor Bahria University Islamabad PK Center of Computer Vision and Pattern Recognition Bahria University Islamabad Pakistan Dept. of Professional Psychology Bahria University Islamabad Pakistan

Drawing tests have been long used by practitioners for early screening of a number of psychological and neurological impairments. These brain functioning tests are used by psychologists to understand feelings, personality and reactions of individuals to different circumstances. Among these, Human Figure Drawing Test (HFDT) is a popular instrument for the assessment of cognitive functioning of individuals. While the HFDT has various dimensions, the focus of this study lies on the face of the drawn figure. A computerized system that analyzes the hand-drawn facial images to extract the expressions from the image is proposed. Sketch of human face is drawn by the subject and then fed to the system, the image is then binarized and segmented into different facial components. Features (based on local binary patterns, gray level co-occurrence matrices and histogram of oriented gradients) computed from the facial components are used to train an SVM classifier to learn to distinguish between four expression classes, `happy', `sad', `angry' and `neutral'. The system evaluated on a custom developed database of sketches realized promising results. The developed system could serve as a useful module toward development of a complete automated system to score human figure drawing test.

关键词： Feature extraction Psychology Face recognition Face Databases Support vector machines Lips

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Gender Classification from Offline Handwriting Images Using Textural Features

Gender Classification from Offline Handwriting Images Using ...

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International Workshop on Frontiers in Handwriting recognition

作者： Ali Mirza Momina Moetesum Imran Siddiqi Chawki Djeddi Center of Computer Vision and Pattern Recognition Bahria University Islamabad Pakistan LAMIS Laboratory Larbi Tebessi University Tebessa Algeria

ISBN: (纸本)9781509009824

Prediction of gender and other demographic attributes of individuals from handwriting samples offers an interesting basic, as well as applied research problem. The correlation between gender and the visual appearance of handwriting has been validated by a number of studies and the present study is based on the same idea. We exploit the textural measurements as the discriminating attribute between male and female writings. The textural information in a writing is captured by applying a bank of Gabor filters to the image of handwriting. The mean and standard deviation values of the filter responses are collected in matrix and the Fourier transform of the matrix is used as a feature. Classification is carried out using a feed forward neural network. The proposed technique evaluated on a subset of the QUWI database realized promising results under different experimental settings.

关键词： Writing Databases Feature extraction Visualization Training Correlation Standards

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Video Script Identification Using a Combination of Textural Features

Video Script Identification Using a Combination of Textural ...

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International IEEE Conference on Signal-Image Technologies and Internet-Based System

作者： Zumra Malik Ali Mirza Akram Bennour Imran Siddiqi Chawki Djeddi Center of Computer Vision & Pattern Recognition Bahria University Islamabad Pakistan Departement of Mathematics and Computer Science Larbi Tebessi University Tebessa Algeria

This paper presents a system for script recognition of the text appearing in video frames. The textual content in videos is generally extracted and recognized for development of text based indexing and retrieval systems. If the text in videos appears only in a single script, the output of text detector is directly fed to a video Optical Character recognition (OCR) system for recognition. However, in cases where text may appear in multiple scripts, a script recognition module is required to recognize the script of the text so that it can be processed by the respective OCR. We propose a video script recognition system that considers text in each script as a unique texture. A number of texture measures are extracted from text blocks and an artificial neural network is trained to learn to distinguish between different scripts. The system evaluated on video text blocks in five different scripts (Arabic, English, Urdu, Hindi and Chinese) reported promising recognition rates. In addition to the performance of individual textural features, different combinations of texture measures were investigated which realized interesting results.

关键词： Text recognition Image recognition Histograms Optical character recognition software Fractals Character recognition Indexing

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Convex hull based approach for multi-oriented character recognition from graphical documents

Convex hull based approach for multi-oriented character reco...

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作者： Roy, Partha Pratim Pal, Umapada Lladós, Josep Kimura, Fumitaka Computer Vision Center Universitat Autònoma De Barcelona 08193 Bellaterra Spain Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata - 108 India Graduate School of Engineering Mie University 1577 Kurimamachiya Mie 514-8504 Japan

ISBN: (纸本)9781424421756

In this paper, we present a scheme towards recognition of English character in multi-scale and multi-oriented environments. Graphical document such as map consists of text lines which appear in different orientation. Sometimes, characters in a single word may follow a curvi-linear way to annotate the graphical curve lines. For recognition of such multi-scale and multi-oriented characters a Support Vector Machine (SVM) based scheme is presented in this paper. The feature used here is invariant to character orientation. Circular ring and convex hull have been used along with angular information of the contour pixels of the character to make the feature rotation invariant. We tested our proposed scheme on two different datasets. Combining circular and convex hull feature we have obtained 96.73% and 99.56% accuracy in these two datasets. © 2008 IEEE.

关键词： Support vector machines

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Automated scoring of Bender Gestalt Test using image analysis techniques

Automated scoring of Bender Gestalt Test using image analysi...

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International Conference on Document Analysis and recognition

作者： Momina Moetesum Imran Siddiqi Uzma Masroor Chawki Djeddi Center of Computer Vision and Pattern Recognition Bahria University Islamabad Pakistan Dept. of Professional Psychology Bahria University Islamabad Pakistan LAMIS Laboratory Larbi Tebessi University Tebessa Algeria

ISBN: (纸本)9781479918065

Drawing tests have been long used by practitioners and researchers for early detection of psychological and neurological impairments. These tests allow subjects to naturally express themselves as opposed to an interview or a written assessment. Bender Gestalt Test (BGT) is a well-known and established neurological test designed to detect signs of perceptual distortions. Subjects are shown a number of geometric patterns for reconstruction and assessments are made by observing properties like rotation, angulations, simplification and closure difficulty. The manual scoring of the test, however, is a time consuming and lengthy procedure especially when a large number of subjects is to be analyzed. This paper proposes the application of image analysis techniques to automatically score a subset of hand drawn images in the BGT test. A comparison of the scores reported by the automated system with those assigned by the psychologists not only reveals the effectiveness of the proposed system but also reflects the huge research potential this area possesses.

关键词： Manuals Psychology Biomedical imaging Computational modeling

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