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Journal articles on the topic 'Active shape model, ASM'

Author: Grafiati

Published: 24 April 2022

Last updated: 30 July 2025

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1

Naoui, Moulkheir, and Ghalem Belalem. "Intensity Profiles in Active Shape Model." Revue d'Intelligence Artificielle 34, no. 5 (2020): 531–39. http://dx.doi.org/10.18280/ria.340502.

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Active shape model is a deformable model which has proven very successful results in the field of image segmentation. The success of ASM model lies in its ability to find the right positions of all landmark points which define the object shape. Intensity profiles are an important part of the Active Shape Models (ASM) which help steer and optimize matching process. However, their simplicity in the standard version of the ASM turns into weakness. The difficulties are met when they are applied to complex structures. The main purpose of this paper is to give a review and discussion about the alter

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Iqtait, M., F. S. Mohamad, and M. Mamat. "Feature extraction for face recognition via Active Shape Model (ASM) and Active Appearance Model (AAM)." IOP Conference Series: Materials Science and Engineering 332 (March 2018): 012032. http://dx.doi.org/10.1088/1757-899x/332/1/012032.

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A. Aly, Ashraf. "Cell Tracking Quality Comparison Between Active Shape Model (ASM) and Active Appearance Models (AAM) - Based Tracking." International Journal of Information Technology Convergence and Services 6, no. 4 (2016): 17–28. http://dx.doi.org/10.5121/ijitcs.2016.6402.

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Gu, Xue Jing, Yue Hua Zhang, and Bei Bei Gao. "Application of Improved ASM and AAM Fusion in Face Tracking." Advanced Materials Research 1014 (July 2014): 463–66. http://dx.doi.org/10.4028/www.scientific.net/amr.1014.463.

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Based on the active shape model(ASM) and active appearance model(AAM) algorithm, using the AAM texture matching for global search and ASM feature points localization of local search, a new algorithm that combining the characteristics of both is adopted. This algorithm ensures the accuracy of feature point positioning and enhanced the texture matching accuracy, improved the tracking accuracy and quickness when target partially obscured and nearby background change in the process of face tracking effectively. Experimental results show that the algorithm improved the precision and robustness grea

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Wang, Chang Yuan, Jing Wang, and Mei Juan Qu. "Active Shape and Active Apparent Hybrid Model of Human Facial Feature Points Localization Algorithm." Applied Mechanics and Materials 220-223 (November 2012): 2284–87. http://dx.doi.org/10.4028/www.scientific.net/amm.220-223.2284.

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An improved active shape model (ASM) and active appearance model (AAM) based new method is proposed, this method will use two-dimensional local gray information to update the feature point position when using ASM to locate the face contour feature points. As to the internal features point location, it establishes facial organs independent AAM model. At the same time, it uses different measure functions to judge the convergence of search algorithm. The experimental results show that the new algorithm greatly improved the localization accuracy of facial feature points.

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ALEMY, ROGHAYEH, MOHAMMAD EBRAHIM SHIRI, FARZAD DIDEHVAR, and ZEYNAB HAJIMOHAMMADI. "NEW FACIAL FEATURE LOCALIZATION ALGORITHM USING ADAPTIVE ACTIVE SHAPE MODEL." International Journal of Pattern Recognition and Artificial Intelligence 26, no. 01 (2012): 1256003. http://dx.doi.org/10.1142/s0218001412560034.

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One of the important steps in/towards face recognition is facial feature localization which is difficult. The variety of human faces, expressions, facial hair, race, glasses, poses, and lighting contribute to the complexity of the problem. We systematically varied some of these factors to test the performance of the original active shape model (ASM) and in the next step we modified original ASM that improved accuracy of ASM. Due to these modifications, a new scheme of active shape model for facial feature extraction is proposed in this paper which is named adaptive active shape model. In this

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Chen, Hengxin, Mingqi Gao, and Bin Fang. "An improved active shape model method for facial landmarking based on relative position feature." International Journal of Wavelets, Multiresolution and Information Processing 15, no. 01 (2017): 1750008. http://dx.doi.org/10.1142/s0219691317500084.

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Active Shape Model (ASM) is a most effective method of facial landmarking. It employs two models, profile model and shape model, to match the position of facial landmark. In this paper, we introduce a new model based on relative position feature (RPF) in local region to improve ASM. We found the fact that landmarks with larger matching error have more shape matching displacement. So, in our method, RPF model is used to adjust the position of landmarks with more shape matching displacement in every matching iteration. STASM (Stacked ASM) is practical standard of ASM and is proved to be the best

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Meng, Siming. "Research into Human Face Recognition Algorithm Based on Active Appearance Model Feature Positioning." Journal of Computational and Theoretical Nanoscience 13, no. 10 (2016): 7554–63. http://dx.doi.org/10.1166/jctn.2016.5753.

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Active Appearance Model (AAM) is a valid statistical algorithm for human face alignment, which composes of two parts, namely AAM sub-space model and AAM searching process. AAM has three sub-spaces, namely form sub-space, texture sub-space and surface sub-face. As it is stated above, AAM is built on the dot distribution model. Different from ASM, it not only conducts statistical analysis of textures through the shape information, but also explores the connection between the shape and the texture. During the training period, it mainly targets at finding out the connection between model parameter

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Dr., D. Naga Ravikiran, Bhagya Lakshmi Ch, Siva Rama Krishna A, Gopala Krishna M, and Jaswanth K. "Parametric Facial Landmark Detection Using Active Shape Models." International Journal for Modern Trends in Science and Technology 11, no. 03 (2025): 79–85. https://doi.org/10.5281/zenodo.15084856.

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Facial landmark detection plays a vital role in various applications, including face recognition and 3D face reconstruction. In this study, we introduce a parametric approach based on Active Shape Models (ASM) for facial landmark detection. Specifically, we encode landmark locations using ASM parameters and employ cascade regression to estimate these parameters. The final landmark positions are then derived from the ASM parameters. This parametric formulation offers a more compact and efficient representation compared to existing methods. Experimental results validate the effectiveness of our

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Marcella, Peter, Minoi Jacey-Lynn, and Ab Rahman Suriani. "Neutral expression synthesis using kernel active shape model." Indonesian Journal of Electrical Engineering and Computer Science 20, no. 1 (2022): 150–57. https://doi.org/10.11591/ijeecs.v20.i1.pp150-157.

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This paper presents a modified kernel-based Active Shape Model for neutralizing and synthesizing facial expressions. In recent decades, facial identity and emotional studies have gained interest from researchers, especially in the works of integrating human emotions and machine learning to improve the current lifestyle. It is known that facial expressions are often associated with face recognition systems with poor recognition rate. In this research, a method of a modified kernel-based active shape model based on statistical-based approach is introduced to synthesize neutral (neutralize) expre

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Wang, Chang Yuan, Mei Juan Qu, Hong Bo Jia, and Hong Zhe Bi. "Facial Feature Detection Algorithm Based on Main Characteristics of Eyes." Applied Mechanics and Materials 303-306 (February 2013): 1402–5. http://dx.doi.org/10.4028/www.scientific.net/amm.303-306.1402.

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This paper proposed a new facial feature points localization algorithm based on main characteristics of eyes.Use the result of pupil center position to initialize the model of hybrid improved active shape model (ASM) and active appearance model (AAM). The algorithm will use two-dimensional local gray information to update the feature point position when using ASM to locate the face contour feature points. As to the internal features point location, it establishes facial organs independent AAM model. At the same time, it optimizes measure functions of ASM and AAM to judge the convergence of sea

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Zhai, Guang Fei, Guang Da Su, and Jiong Xin Liu. "Research of Facial Features Extraction Based on Improved ASM." Advanced Materials Research 271-273 (July 2011): 131–36. http://dx.doi.org/10.4028/www.scientific.net/amr.271-273.131.

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Traditional ASM (Active Shape Model) methods usually depend heavily on the initial facial landmark positions located by the face detector. During the fitting process the ASM model may be trapped into local optima instead of the global optima due to the inaccurate initial position selection. In this paper we present that this problem can be solved by incorporating pupil and chin localizations in adjusting the initial landmark positions, together with adaptive step length selection based on two-dimensional gradient characteristic in a multi-scale ASM model. Experiments on a face database consist

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Sun, Shenshen, Huizhi Ren, Tian Dan, and Wu Wei. "3D segmentation of lungs with juxta-pleural tumor using the improved active shape model approach." Technology and Health Care 29 (March 25, 2021): 385–98. http://dx.doi.org/10.3233/thc-218037.

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BACKGROUND AND OBJECTIVE: At present, there are many methods for pathological lung segmentation. However, there are still two unresolved problems. (1) The search steps in traditional ASM is a least square optimization method, which is sensitive to outlier marker points, and it makes the profile update to the transition area in the middle of normal lung tissue and tumor rather than a true lung contour. (2) If the noise images exist in the training dataset, the corrected shape model cannot be constructed. METHODS: To solve the first problem, we proposed a new ASM algorithm. Firstly, we detected

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Lee, Jiann-Shu, Hsing-Hsien Wu, and Ming-Zheng Yuan. "LUNG SEGMENTATION FOR CHEST RADIOGRAPH BY USING ADAPTIVE ACTIVE SHAPE MODELS." Biomedical Engineering: Applications, Basis and Communications 22, no. 02 (2010): 149–56. http://dx.doi.org/10.4015/s1016237210001876.

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In this article, we propose an automatic lung segmentation method. We design an ROI-adjusted initial boundary derivation method to estimate a proper initial lung boundary for ASM deformation by deriving the translation and the scaling parameters from the lung ROI. An adaptive ASM, using k-means clustering and silhouette-based cluster validation technique, is proposed to adapt to the lung shape change so that the lung shape variation among people can be overwhelmed. The experimental results indicate that the performance of the proposed lung segmentation method is superior to the traditional ASM

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Gill, Gurman, Matthew Toews, and Reinhard R. Beichel. "Robust Initialization of Active Shape Models for Lung Segmentation in CT Scans: A Feature-Based Atlas Approach." International Journal of Biomedical Imaging 2014 (2014): 1–7. http://dx.doi.org/10.1155/2014/479154.

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Model-based segmentation methods have the advantage of incorporating a priori shape information into the segmentation process but suffer from the drawback that the model must be initialized sufficiently close to the target. We propose a novel approach for initializing an active shape model (ASM) and apply it to 3D lung segmentation in CT scans. Our method constructs an atlas consisting of a set of representative lung features and an average lung shape. The ASM pose parameters are found by transforming the average lung shape based on an affine transform computed from matching features between t

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Zhang, X., B. Xiong, and G. Kuang. "AIRCRAFT SEGMENTATION IN SAR IMAGES BASED ON IMPROVED ACTIVE SHAPE MODEL." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3 (April 30, 2018): 2331–35. http://dx.doi.org/10.5194/isprs-archives-xlii-3-2331-2018.

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In SAR image interpretation, aircrafts are the important targets arousing much attention. However, it is far from easy to segment an aircraft from the background completely and precisely in SAR images. Because of the complex structure, different kinds of electromagnetic scattering take place on the aircraft surfaces. As a result, aircraft targets usually appear to be inhomogeneous and disconnected. It is a good idea to extract an aircraft target by the active shape model (ASM), since combination of the geometric information controls variations of the shape during the contour evolution. However

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Sun, Yan Peng. "Human Facial Feature Point Detection is Based on Improved ASM Method." Advanced Materials Research 181-182 (January 2011): 139–44. http://dx.doi.org/10.4028/www.scientific.net/amr.181-182.139.

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In view of the traditional Active Shape Model (ASM) method’s flaw and insufficiency, the paper proposed several improvements methods. The traditional ASM method carries on the characteristic search using of the initial point which provided using the person face examination；in the improvement algorithm, the paper has used the method of pupil orientation on the initialization and adopted improvement methods of edge restraint, auto-adapted length of stride to effectively improved the ASM method performance. The experimental result indicated that, the improvement ASM method has a bigger enhancemen

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VELASCO, HORACIO MANUEL GONZÁLEZ, CARLOS JAVIER GARCÍA ORELLANA, FRANCISCO JAVIER LÓPEZ ALIGUÉ, MIGUEL MACÍAS MACÍAS, and RAMÓN GALLARDO CABALLERO. "SEGMENTATION OF BOVINE LIVESTOCK IMAGES USING GA AND ASM IN A TWO-STEP APPROACH." International Journal of Pattern Recognition and Artificial Intelligence 17, no. 04 (2003): 601–16. http://dx.doi.org/10.1142/s0218001403002575.

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In this work a system based on genetic algorithms (GA) and active shape models (ASM) is presented that, in a two-step approach, is able to accurately find a particular object within the image. The aim of the first stage is to approximately locate the object in order to serve as an initialization for the second. Following a method similar to that used by other authors, a model of the desired shape (cows in lateral position) is constructed using PDM, and later the search within the image is carried out based on instances of that model, and using genetic algorithm techniques, for which several ob

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Salman Al-Shaikhli, Saif Dawood, Michael Ying Yang, and Bodo Rosenhahn. "3D automatic liver segmentation using feature-constrained Mahalanobis distance in CT images." Biomedical Engineering / Biomedizinische Technik 61, no. 4 (2016): 401–12. http://dx.doi.org/10.1515/bmt-2015-0017.

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Abstract Automatic 3D liver segmentation is a fundamental step in the liver disease diagnosis and surgery planning. This paper presents a novel fully automatic algorithm for 3D liver segmentation in clinical 3D computed tomography (CT) images. Based on image features, we propose a new Mahalanobis distance cost function using an active shape model (ASM). We call our method MD-ASM. Unlike the standard active shape model (ST-ASM), the proposed method introduces a new feature-constrained Mahalanobis distance cost function to measure the distance between the generated shape during the iterative ste

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Antonio Velázquez, Juan Alberto, Marcelo Romero Huertas, Roberto Alejo Eleuterio, Everardo Efrén Granda Gutiérrez, Federico Del Razo López, and Eréndira Rendón Lara. "Pedestrian Localization in a Video Sequence Using Motion Detection and Active Shape Models." Applied Sciences 12, no. 11 (2022): 5371. http://dx.doi.org/10.3390/app12115371.

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There is increasing interest in video object detection for many situations, such as industrial processes, surveillance systems, and nature exploration. In this work, we were concerned with the detection of pedestrians in video sequences. The aim was to deal with issues associated with the background, scale, contrast, or resolution of the video frames, which cause inaccurate detection of pedestrians. The proposed method was based on the combination of two techniques: motion detection by background subtraction (MDBS) and active shape models (ASM). The MDBS technique aids in the identification of

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Yang, Xin, Jiaoying Jin, Mengling Xu, et al. "Ultrasound Common Carotid Artery Segmentation Based on Active Shape Model." Computational and Mathematical Methods in Medicine 2013 (2013): 1–11. http://dx.doi.org/10.1155/2013/345968.

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Carotid atherosclerosis is a major reason of stroke, a leading cause of death and disability. In this paper, a segmentation method based on Active Shape Model (ASM) is developed and evaluated to outline common carotid artery (CCA) for carotid atherosclerosis computer-aided evaluation and diagnosis. The proposed method is used to segment both media-adventitia-boundary (MAB) and lumen-intima-boundary (LIB) on transverse views slices from three-dimensional ultrasound (3D US) images. The data set consists of sixty-eight, 17 × 2 × 2, 3D US volume data acquired from the left and right carotid arteri

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Chen, Xinjian, Jayaram K. Udupa, Abass Alavi, and Drew A. Torigian. "GC-ASM: Synergistic integration of graph-cut and active shape model strategies for medical image segmentation." Computer Vision and Image Understanding 117, no. 5 (2013): 513–24. http://dx.doi.org/10.1016/j.cviu.2012.12.001.

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Busch, S. "ACTIVE SHAPE MODEL PRECISION ANALYSIS OF VEHICLE DETECTION IN 3D LIDAR POINT CLOUDS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W13 (June 4, 2019): 21–26. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w13-21-2019.

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<p><strong>Abstract.</strong> LiDAR systems are frequently used for driver assistance systems. The minimal distance to other objects and the exact pose of a vehicle is important for ego movement prediction. Therefore, in this work, we extract the poses of vehicles from LiDAR point clouds. To this end, we measure them with LiDAR, segment the vehicle points and extract the pose. Further, we analyze the influence of LiDAR resolutions on the pose extraction by active shape models (ASM) and by the center of bounding boxes combined with the principal component analysis (BC-PCA).&lt

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Gómez, Eduardo Galicia, Fabián Torres-Robles, Jorge Perez-Gonzalez, and Fernando Arámbula Cosío. "“ShapeNet”: A Shape Regression Convolutional Neural Network Ensemble Applied to the Segmentation of the Left Ventricle in Echocardiography." Journal of Imaging 11, no. 5 (2025): 165. https://doi.org/10.3390/jimaging11050165.

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Left ventricle (LV) segmentation is crucial for cardiac diagnosis but remains challenging in echocardiography. We present ShapeNet, a fully automatic method combining a convolutional neural network (CNN) ensemble with an improved active shape model (ASM). ShapeNet predicts optimal pose (rotation, translation, and scale) and shape parameters, which are refined using the improved ASM. The ASM optimizes an objective function constructed from gray-level profiles concatenated into a single contour appearance vector. The model was trained on 4800 augmented CAMUS images and tested on both CAMUS and E

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Wu, Jie, Qing He, Ran Zhou, Chao Hu, and Q. H. Meng. "A Novel Method of Extracting Facial Feature Points Based on 3D Rotation and ASM." Applied Mechanics and Materials 58-60 (June 2011): 1466–70. http://dx.doi.org/10.4028/www.scientific.net/amm.58-60.1466.

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Precise extraction of facial feature points is fundamental to a variety of applications including face processing and human-machine interface. In this paper, a novel method of extracting facial feature points for profile faces is presented. This program is mainly based on a 3D rotation model of head and Active Shape Model (ASM). First we transform a profile face to a corresponding frontal face. Then, we implement the ASM program on the frontal face image. According to the relation between the profile face and frontal face, the final position of feature points on the profile face is obtained. W

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Li, Yong, and Qing Zhu Wang. "Matrix Patterns Based Active Appearance Models for Lung CT Segmentation." Advanced Materials Research 1049-1050 (October 2014): 1312–15. http://dx.doi.org/10.4028/www.scientific.net/amr.1049-1050.1312.

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Segmentation of diseased lungs in CT images is a nontrivial problem. As Active Appearance Model (AAM) has been applied effectively in this field, we propose a new approach for the construction of traditional AAM to segment the lung fields more accurately and efficiently: Matrixes based AAM (MatAAM). MatAAM is based on two-dimensional image matrixes rather one-dimensional vectors. Its appearance matrix does not need to be transformed into a vector prior to computing the appearance parameter. Instead, a covariance matrix is constructed directly using the normalized appearance matrixes and its ei

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Shan, Jin Bao, Wei Wei Jiang, and Shi Le Mu. "A New Method of Face Modeling with Construction of Local Texture Model." Advanced Materials Research 989-994 (July 2014): 2016–19. http://dx.doi.org/10.4028/www.scientific.net/amr.989-994.2016.

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The active shape model (ASM) is a statistical parametric model, which is mainly used in image feature extraction. On the basis of the analysis of the original ASM texture model, a new texture modeling method was proposed in this paper. The improved method fully utilized the gray level information of adjacent points in the neighborhood of sampling points, improved the original face modeling method which only used the one-dimensional gray information with model matching accuracy problems. The experiments on Weizmann face database Indicate that, the improved method can obviously improve the featu

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Koo, Ja-Myoung, and Tai-Hoon Cho. "A Virtual Makeup Program Using Facial Feature Area Extraction Based on Active Shape Model and Modified Alpha Blending." Journal of the Korean Institute of Information and Communication Engineering 14, no. 8 (2010): 1827–35. http://dx.doi.org/10.6109/jkiice.2010.14.8.1827.

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Wen, Junling, Miao Jiang, Yihui Wang, Na Huang, and Ming Gao. "An auricular division method based on ASM algorithm." Technology and Health Care 29 (March 25, 2021): 487–95. http://dx.doi.org/10.3233/thc-218046.

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BACKGROUND: Auricular acupuncture point (AAP) therapy is an important part of traditional Chinese medicine and is featured with a sophisticated location method based on the division of auricular subzones. OBJECTIVE: This study aimed to realize the automatic computerized division on the relatively small area of the research object which has long been considered difficult. METHOD: We propose a novel method based on the active shape model algorithm and the “Name and location of AAPs” issued by the World Federation of Acupuncture-Moxibustion Societies (WFAS STANDARD-002:2013). RESULTS: The experim

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Darby, John, Emma F. Hodson-Tole, Nicholas Costen, and Ian D. Loram. "Automated regional analysis of B-mode ultrasound images of skeletal muscle movement." Journal of Applied Physiology 112, no. 2 (2012): 313–27. http://dx.doi.org/10.1152/japplphysiol.00701.2011.

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To understand the functional significance of skeletal muscle anatomy, a method of quantifying local shape changes in different tissue structures during dynamic tasks is required. Taking advantage of the good spatial and temporal resolution of B-mode ultrasound imaging, we describe a method of automatically segmenting images into fascicle and aponeurosis regions and tracking movement of features, independently, in localized portions of each tissue. Ultrasound images (25 Hz) of the medial gastrocnemius muscle were collected from eight participants during ankle joint rotation (2° and 20°), isomet

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Liu, Zhi, Hongjun Wang, and Wei Jiang. "Automated tongue area detection for computer‐aided diagnosis based on ASM and GA." Sensor Review 32, no. 1 (2012): 39–46. http://dx.doi.org/10.1108/02602281211197134.

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PurposeThe human tongue is a unique organ that can be stuck out of the body for physical examination, and tongue diagnosis is very important in traditional Chinese medicine. Automated tongue area detection is crucial and indispensable for computer‐aided tongue diagnosis, but it is difficult to implement because of the physiological properties of the tongue. For example, as a non‐rigid organ, the tongue has a high degree of variability in size, shape, color, and texture. The purpose of this study is to address this problem.Design/methodology/approachThis paper presents a hybrid framework for to

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S., Subhashini, and Revathi S. "A New Fusion Feature Selection Model (FFSM) based Feature Extraction System for Hand Gesture Recognition." Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications 14, no. 4 (2023): 149–63. http://dx.doi.org/10.58346/jowua.2023.i4.011.

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The research presented here proposes a unique approach for exact feature extraction that makes use of the Fusion Feature Selection Model (FFSM). The method encompasses various stages to preprocess and extract crucial features from first-person hand action (FHPA) images. Preprocessing involves video-to-frame conversion, RGB to grayscale conversion, an improved median filter, and Gaussian blur-based image smoothing. Segmentation is achieved using the Improved SwinNet to identify meaningful regions within the images. Feature extraction employs the Gabor Line Derivative (GLD) method, Active Shape

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Salvi, Massimo, Bruno De Santi, Bianca Pop, et al. "Integration of Deep Learning and Active Shape Models for More Accurate Prostate Segmentation in 3D MR Images." Journal of Imaging 8, no. 5 (2022): 133. http://dx.doi.org/10.3390/jimaging8050133.

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Magnetic resonance imaging (MRI) has a growing role in the clinical workup of prostate cancer. However, manual three-dimensional (3D) segmentation of the prostate is a laborious and time-consuming task. In this scenario, the use of automated algorithms for prostate segmentation allows us to bypass the huge workload of physicians. In this work, we propose a fully automated hybrid approach for prostate gland segmentation in MR images using an initial segmentation of prostate volumes using a custom-made 3D deep network (VNet-T2), followed by refinement using an Active Shape Model (ASM). While the

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Fu, JinFeng, and Hongli Zhang. "Personality Trait Detection Based on ASM Localization and Deep Learning." Scientific Programming 2021 (August 20, 2021): 1–11. http://dx.doi.org/10.1155/2021/5675917.

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Global competition is the competition of human resources, the social demand for high-quality talents is increasing, and the demand for all kinds of talents is increasing. Therefore, how to scientifically and efficiently complete the preliminary screening of college students’ mental health, so as to provide services for them, has become an important task. In order to solve the above problems, by combining the relevant professional knowledge of psychology, statistics, image processing, and artificial intelligence technology, a personality trait detection method based on active shape model (ASM)

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Rizwan, Syeda Amna, Ahmad Jalal, Munkhjargal Gochoo, and Kibum Kim. "Robust Active Shape Model via Hierarchical Feature Extraction with SFS-Optimized Convolution Neural Network for Invariant Human Age Classification." Electronics 10, no. 4 (2021): 465. http://dx.doi.org/10.3390/electronics10040465.

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The features and appearance of the human face are affected greatly by aging. A human face is an important aspect for human age identification from childhood through adulthood. Although many traits are used in human age estimation, this article discusses age classification using salient texture and facial landmark feature vectors. We propose a novel human age classification (HAC) model that can localize landmark points of the face. A robust multi-perspective view-based Active Shape Model (ASM) is generated and age classification is achieved using Convolution Neural Network (CNN). The HAC model

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Meziane, Abdelfettah, Saïd MAHMOUDI, and Mohammed Amine CHIKH. "Brain Structures Segmentation by using Statistical Models." Medical Technologies Journal 1, no. 3 (2017): 59. http://dx.doi.org/10.26415/2572-004x-vol1iss3p59-59.

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Automatic segmentation of brain structures is a fundamental step for quantitative analysis of images in many brain’s pathologies such as Alzheimer’s, brain’s tumors or multiple sclerosis. The large variation of brain structures requires the development of efficient and specific methods, often by using Magnetic Resonance Imaging (MRI) modality. The goal of our work is to implement an automatic brain’s structures segmentation method that uses the active shape models (ASM) and active appearance models (AAM) techniques. Another goal of this work is to compare the performances of these segmentation

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Peter, Marcella, Jacey-Lynn Minoi, and Suriani Ab Rahman. "Neutral expression synthesis using kernel active shape model." Indonesian Journal of Electrical Engineering and Computer Science 20, no. 1 (2020): 150. http://dx.doi.org/10.11591/ijeecs.v20.i1.pp150-157.

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This paper presents a modified kernel-based Active Shape Model for neutralizing and synthesizing facial expressions. In recent decades, facial identity and emotional studies have gained interest from researchers, especially in the works of integrating human emotions and machine learning to improve the current lifestyle. It is known that facial expressions are often associated with face recognition systems with poor recognition rate. In this research, a method of a modified kernel-based active shape model based on statistical-based approach is introduced to synthesize neutral (neutralize) expre

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Fatihin, Mohammad Meizaki, Farid Baskoro, and Arif Widodo. "KLASIFIKASI OSTEOARTHRITIS BERBASIS DUAL TREE COMPLEX WAVELET TRANSFORM DAN CONTRAST LIMITED ADAPTIVE HISTOGRAM EQUALIZATION (CLAHE) MENGGUNAKAN ACTIVE SHAPE MODELS." INAJEEE Indonesian Journal of Electrical and Eletronics Engineering 3, no. 1 (2020): 15. http://dx.doi.org/10.26740/inajeee.v3n1.p15-24.

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Citra adalah representasi dari informasi yang terkandung di dalamnya sehingga mata manusia dapat menganalisis dan menafsirkan informasi sesuai dengan tujuan yang diharapkan. Salah satu bentuk citra medis adalah citra x-ray. Penelitian ini mengidentifikasi gambar x-ray Osteoarthritis Lutut yang diambil pada berbagai tingkat keparahan, mulai dari KL-Grade 0 hingga KL-Grade 4. Penelitian ini menggunakan metode CLAHE dan DTCWT untuk proses preprosessing dan menggunakan metode Active Shape Model (ASM) untuk proses segmentasi, menggunakan 35 data pelatihan dan 200 data uji dari Osteoarthritis Initia

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SU, YA, and XINBO GAO. "ITERATIVE SHAPE REFINEMENT IN AAM." International Journal of Image and Graphics 11, no. 01 (2011): 137–51. http://dx.doi.org/10.1142/s0219467811004032.

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Active appearance model (AAM) is a powerful model to describe deformable objects in terms of shape and texture. It models the shape and the texture variations linearly and independently and has been widely applied to pattern recognition. However, there are two problems in the model building procedure. On the one hand, much shape information is lost from the shape model because only the sparse landmarks manually labeled are taken into account. On the other hand, the high-dimensional texture has too much nonlinearity. It is resulted from the structure information left by the shape model. In this

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Sri, Widodo, Nur Rohmah Ratnasari, Handaga Bana, and Dyah Dewi Arini Liss. "Lung diseases detection caused by smoking using support vector machine." TELKOMNIKA Telecommunication, Computing, Electronics and Control 17, no. 3 (2019): 1256–66. https://doi.org/10.12928/TELKOMNIKA.v17i3. 9799.

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Type of lung disease is very much manifold, but type of lung disease caused by smoking there are only 4, namely Bronchitis, Pneumonia, Emphysema and Lung Cancer. Doctors usually diagnose lung disease from CT scans using the naked eye, then interpret data one by one.This procedure is not effective. The aim of this research is improvement accuracy of lung diseases detection caused by smoking using support vector machine on computed tomography scan (CT scan) images. This study includes 4 (four) main points. First is the development of software for segmentation of lung organ automatically using Ac

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Islam, Md Rabiul, and Md Abdus Sobhan. "Feature Fusion Based Audio-Visual Speaker Identification Using Hidden Markov Model under Different Lighting Variations." Applied Computational Intelligence and Soft Computing 2014 (2014): 1–7. http://dx.doi.org/10.1155/2014/831830.

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The aim of the paper is to propose a feature fusion based Audio-Visual Speaker Identification (AVSI) system with varied conditions of illumination environments. Among the different fusion strategies, feature level fusion has been used for the proposed AVSI system where Hidden Markov Model (HMM) is used for learning and classification. Since the feature set contains richer information about the raw biometric data than any other levels, integration at feature level is expected to provide better authentication results. In this paper, both Mel Frequency Cepstral Coefficients (MFCCs) and Linear Pre

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Sembdner, Philipp, Bernhard Bust, Lars Dornheim, Stefan Holtzhausen, and Ralph Stelzer. "Smart surgical template models for customized knee joint replacements." Current Directions in Biomedical Engineering 7, no. 2 (2021): 129–32. http://dx.doi.org/10.1515/cdbme-2021-2033.

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Abstract The paper introduces a method for the automated generation of patient-specific instruments (PSI), here in particular templates, for the implantation of customized implants. The basis is the derivation of data from the morphology of the bony situation and the medical planning. A developed methodological approach based on an Active Shape Model (ASM) is used for the morphological measurement. Determined geometric dimensions are placed on this ASM and automatically adjusted in each case. In addition, specially developed software tools for the planning and design of medical devices will be

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Sabir, Zulqurnain, Muhammad Asif Zahoor Raja, Thongchai Botmart, and Wajaree Weera. "A Neuro-Evolution Heuristic Using Active-Set Techniques to Solve a Novel Nonlinear Singular Prediction Differential Model." Fractal and Fractional 6, no. 1 (2022): 29. http://dx.doi.org/10.3390/fractalfract6010029.

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In this study, a novel design of a second kind of nonlinear Lane–Emden prediction differential singular model (NLE-PDSM) is presented. The numerical solutions of this model were investigated via a neuro-evolution computing intelligent solver using artificial neural networks (ANNs) optimized by global and local search genetic algorithms (GAs) and the active-set method (ASM), i.e., ANN-GAASM. The novel NLE-PDSM was derived from the standard LE and the PDSM along with the details of singular points, prediction terms and shape factors. The modeling strength of ANN was implemented to create a merit

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Ceresa, Claudia C., Alan J. Knox, and Simon R. Johnson. "Use of a three-dimensional cell culture model to study airway smooth muscle-mast cell interactions in airway remodeling." American Journal of Physiology-Lung Cellular and Molecular Physiology 296, no. 6 (2009): L1059—L1066. http://dx.doi.org/10.1152/ajplung.90445.2008.

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Increased airway smooth muscle (ASM) mass and infiltration by mast cells are key features of airway remodeling in asthma. We describe a model to investigate the relationship between ASM, the extracellular matrix, mast cells, and airway remodeling. ASM cells were cultured in a three-dimensional (3-D) collagen I gel (3-D culture) alone or with mast cells. Immunocytochemistry and Western blotting of ASM in 3-D cultures revealed a spindle-shaped morphology and significantly lower α-smooth muscle actin and vimentin expression than in ASM cultured in monolayers on collagen type I or plastic (2-D cul

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Liang, Yanqiu. "Intelligent Emotion Evaluation Method of Classroom Teaching Based on Expression Recognition." International Journal of Emerging Technologies in Learning (iJET) 14, no. 04 (2019): 127. http://dx.doi.org/10.3991/ijet.v14i04.10130.

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To solve the problem of emotional loss in teaching and improve the teaching effect, an intelligent teaching method based on facial expression recognition was studied. The traditional active shape model (ASM) was improved to extract facial feature points. Facial expression was identified by using the geometric features of facial features and support vector machine (SVM). In the expression recognition process, facial geometry and SVM methods were used to generate expression classifiers. Results showed that the SVM method based on the geometric characteristics of facial feature points effectively

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Li, Wenfeng, Yulin Yuan, Shikang Hu, Mei Li, Wenxiu Feng, and Jiaxin Zheng. "Positioning of Apple’s Growth Cycle Based on Pattern Recognition." Mobile Information Systems 2021 (May 18, 2021): 1–11. http://dx.doi.org/10.1155/2021/9687950.

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The positioning of the apple growth cycle plays a very important role in predicting the development of apples and guiding fruit farmers in agricultural operations. The traditional method of manually positioning the apple growth cycle has problems such as low efficiency and poor accuracy. Pattern recognition provides support for continuous and rapid positioning during the apple growth process. Under the natural conditions of the orchard, due to the large differences in the individual colors of the apples during the growth process and the influence of factors such as light changes, the photograp

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Quivy, Charles-Henri, and Itsuo Kumazawa. "Normalization of Active Appearance Models for Fish Species Identification." ISRN Signal Processing 2011 (June 23, 2011): 1–16. http://dx.doi.org/10.5402/2011/103293.

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In recent years, automatic visual coral reef monitoring has been proposed to solve the demerits of manual monitoring techniques. This paper proposes a novel method to reduce the computational cost of the standard Active Appearance Model (AAM) for automatic fish species identification by using an original multiclass AAM. The main novelty is the normalization of species-specific AAMs using techniques tailored to meet with fish species identification. Shape models associated to species-specific AAMs are automatically normalized by means of linear interpolations and manual correspondences between

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Azzaoui, M. A., M. Adnani, H. El Belrhiti, I. E. Chaouki, and L. Masmoudi. "DETECTION OF CRESCENT SAND DUNES CONTOURS IN SATELLITE IMAGES USING AN ACTIVE SHAPE MODEL WITH A CASCADE CLASSIFIER." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W12 (February 21, 2019): 17–24. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w12-17-2019.

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<p><strong>Abstract.</strong> Crescent sand dunes called barchans are the fastest moving sand dunes in the desert, causing disturbance for infrastructure and threatening human settlements. Their study is of great interest for urban planners and geologists interested in desertification (Hugenholtz et al., 2012). In order to study them at a large scale, the use of remote sensing is necessary. Indeed, barchans can be part of barchan fields which can be composed of thousands of dunes (Elbelrhiti et al.2008). Our region of interest is located in the south of Morocco, near the city

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Hsieh, Ching Tang, Chia Shing Hu, and Chun Wei Pan. "Automatic Facial Aging/Rejuvenating Synthesis Method." Applied Mechanics and Materials 284-287 (January 2013): 3035–39. http://dx.doi.org/10.4028/www.scientific.net/amm.284-287.3035.

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At present, the synthesizing faces of different ages does not emphasize on feature alignment and rectification of twisted images. If these situations do happen, they might cause failure and inaccuracy on synthesizing images. In this paper, we propose a reversible human facial aging/rejuvenating synthesis system which is implemented by Active Shape Model (ASM) integrated with Log-Gabor Wavelet, which can be used to search for the dementia elderly. First, we use AdaBoost and ASM algorithm to extract the feature set of human face, and rectify them by the concept of facial geometric invariance. Th

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Zhang, Yong Liang, Shou Gen Zhao, Lun Long, and Kang Li. "Numerical Simulation of Solar Array with Shape Memory Alloy in Active Vibration Control." Applied Mechanics and Materials 29-32 (August 2010): 589–95. http://dx.doi.org/10.4028/www.scientific.net/amm.29-32.589.

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The objective of this study is to develop a general design scheme for shape memory alloys (SMA) intelligent structure. The scheme involves dynamic modeling and closed-loop simulation in a finite element environment. First, the structure of multi-body finite element model simulating the real solar array is established. SMA wire is appended on the model. The physical value of the strain, displacement, velocity and acceleration at the sensors locations separately is acted as the feedback signal. The value is multiplied by the control gain to calculate the voltage inputted to SMA wire. The finite

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