Relevant bibliographies by topics / Improved active shape model (IASM)

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Improved active shape model (IASM)'

Author: Grafiati
Published: 3 June 2025
Last updated: 20 July 2025

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Journal articles on the topic "Improved active shape model (IASM)"

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Hahn, Hee-Il. "Proposing Shape Alignment for an Improved Active Shape Model." Journal of Korea Multimedia Society 15, no. 1 (2012): 63–70. http://dx.doi.org/10.9717/kmms.2012.15.1.063.

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Zhao, Peng, Gang Dou, and Guang-Sheng Chen. "Wood species identification using improved active shape model." Optik 125, no. 18 (2014): 5212–17. http://dx.doi.org/10.1016/j.ijleo.2014.06.047.

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Yang, Fei. "Locating facial features with an improved active shape model." Optical Engineering 48, no. 5 (2009): 057202. http://dx.doi.org/10.1117/1.3130212.

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Wang, Min, Yiling Wen, Li Fang, and Weiping Sun. "An Improved Active Shape Model Application on Facial Feature Localization." International Journal of Information Technology and Computer Science 2, no. 1 (2010): 1–9. http://dx.doi.org/10.5815/ijitcs.2010.01.01.

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Sigit, Riyanto, Calvin Alfa Roji, Tri Harsono, and Son Kuswadi. "Improved echocardiography segmentation using active shape model and optical flow." TELKOMNIKA (Telecommunication Computing Electronics and Control) 17, no. 2 (2019): 809. http://dx.doi.org/10.12928/telkomnika.v17i2.11821.

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ZHENG, Z., J. JIONG, D. CHUNJIANG, X. LIU, and J. YANG. "Facial feature localization based on an improved active shape model." Information Sciences 178, no. 9 (2008): 2215–23. http://dx.doi.org/10.1016/j.ins.2007.12.014.

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Riyanto, Sigit, Alfa Roji Calvin, Harsono Tri, and Kuswadi Son. "Improved echocardiography segmentation using active shape model and optical flow." TELKOMNIKA Telecommunication, Computing, Electronics and Control 17, no. 2 (2019): 809–18. https://doi.org/10.12928/TELKOMNIKA.v17i2.11821.

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Heart disease is one of the most dangerous diseases that threaten human life. The doctor uses echocardiography to analyze heart disease. The result of echocardiography test is a video that shows the movement of the heart rate. The result of echocardiography test indicates whether the patient’s heart is normal or not by identifying a heart cavity area. Commonly it is determined by a doctor based on his own accuracy and experience. Therefore, many methods to do heart segmentation is appearing. But, the methods are a bit slow and less precise. Thus, a system that can help the doctor to anal
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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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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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Tang, Dejun, Weishi Zhang, Xiaolu Qu, and Dongqing Zhang. "Improved active shape model and its application to facial feature extraction." Journal of Electronic Imaging 22, no. 3 (2013): 033023. http://dx.doi.org/10.1117/1.jei.22.3.033023.

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Dissertations / Theses on the topic "Improved active shape model (IASM)"

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Lin, Yu-Hao, and 林宇浩. "Improved Active Shape Model for Facial Component Tracking using Curve Fitting and Dynamic Programming." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/brv445.

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碩士<br>國立東華大學<br>資訊工程學系<br>102<br>Facial Component Extraction (FCE) is a key problem in many Facial information processing (FIP) applications. The Active Shape Model (ASM) is a well-known and commonly-used technique for tackling the problem FCE. The ASM performs the FCE by fitting shapes through facial landmark searching and shape reconstruction. During landmark searching, the ASM considers no local smoothness of shape contours, consequently resulting in some absurdly located facial landmarks which in turn cause poor reconstruction of shapes. Furthermore, as the landmarks are searched by matchi
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Chen, Cong-Huai, and 陳琮淮. "Improved Facial Component Tracking and Extraction by Integrating Active Shape Model and Dynamic Time Warping." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/f9pfcr.

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碩士<br>國立東華大學<br>資訊工程學系<br>100<br>Facial component extraction (FCE) is a key problem in the facial information processing and analyzing (FIPA) because many facial applications require FCE as a preprocessing step. For extracting facial components, the active shape model (ASM) is an option commonly adopted by many researchers. As reported in many studies, the efficacy of ASM significantly depends on the initializing positions of facial landmarks and the finally searched facial landmarks. Badly initialized facial landmarks would not lead to accurate searching of facial landmarks and then cause ina
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Book chapters on the topic "Improved active shape model (IASM)"

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Duta, Nicolae, and Milan Sonka. "An improved active shape model: Handling occlusion and outliers." In Image Analysis and Processing. Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/3-540-63507-6_225.

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Shin, Jeongho, Hyunjong Ki, Vivek Maik, Jinyoung Kang, Junghoon Jung, and Joonki Paik. "Evolutionary Algorithm-Based Local Structure Modeling for Improved Active Shape Model." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-24653-4_37.

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Duta, Nicolae, and Milan Sonka. "Segmentation and interpretation of MR brain images using an improved knowledge-based active shape model." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/3-540-63046-5_29.

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Song, Yili, Die Hu, Qingtao Liu, and Xue Zhang. "An Optimization Model for the Design of Fast Working Face." In Advances in Transdisciplinary Engineering. IOS Press, 2022. http://dx.doi.org/10.3233/atde220101.

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Whether the parabola can be close to an ideal parabolic surface has an important effect on the working efficiency of FAST. In this paper, the influence mechanism of radial expansion of FAST actuator on the shape adjustment of active reflector is analyzed, so as to explore the scheme to determine the ideal working face of FAST. Based on the geometric relations of paraboloids, an optimal model for determining the ideal paraboloid was established, and then euler transformation was carried out on the coordinate positions of the celestial bodies, and the hierarchical iterative algorithm was used to adjust the reflection surface, and the optimal model for adjusting the working paraboloid was established. Finally, the MATLAB was used to solve the model to determine the best working face position of FAST, and calculated that the reception efficiency of the feed cabin after adjustment has been improved by more than 90%. The optimization model established in this paper and the research results of layered iterative algorithm can be used as a reference for the working face adjustment of radio telescope in engineering application.
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Conference papers on the topic "Improved active shape model (IASM)"

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Ayhan, Oner, Bahri Abaci, and Tayfun Akgul. "Improved Active Shape Model for variable illumination conditions." In 2013 IEEE 15th International Workshop on Multimedia Signal Processing (MMSP). IEEE, 2013. http://dx.doi.org/10.1109/mmsp.2013.6659309.

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Hoang, Van-Thanh, and Kang-Hyun Jo. "An improved method for 3D shape estimation using active shape model." In 2017 10th International Conference on Human System Interactions (HSI). IEEE, 2017. http://dx.doi.org/10.1109/hsi.2017.8005035.

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Xu, Hua, and Zheng Ma. "An Improved Active Shape Model for Facial Feature Location." In 2008 Second International Symposium on Intelligent Information Technology Application (IITA). IEEE, 2008. http://dx.doi.org/10.1109/iita.2008.419.

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Liting Wang, Xiaoqing Ding, and Chi Fang. "Generic face alignment using an improved Active Shape Model." In 2008 International Conference on Audio, Language and Image Processing (ICALIP). IEEE, 2008. http://dx.doi.org/10.1109/icalip.2008.4590037.

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Sigit, Riyanto, Setiawardhana, and Shabrina Nurdiani Saleh. "Improved segmentation of cardiac image using active shape model." In 2017 International Seminar on Application for Technology of Information and Communication (iSemantic). IEEE, 2017. http://dx.doi.org/10.1109/isemantic.2017.8251871.

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Wei, Yunlong, and Mei Xie. "An Improved Active Shape Model for Facial Feature Location." In 2009 International Symposium on Computer Network and Multimedia Technology (CNMT 2009). IEEE, 2009. http://dx.doi.org/10.1109/cnmt.2009.5374716.

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Han, Chao, Fucheng You, Shaomei Wang, and Lei Shang. "Improved Search Strategy for Active Shape Model of Face Alignment." In 2019 International Conference on Machine Learning, Big Data and Business Intelligence (MLBDBI). IEEE, 2019. http://dx.doi.org/10.1109/mlbdbi48998.2019.00045.

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Zhang, Fan, Ruimin Shen, Lishuang Xu, Gang Chen, and Jiajun Wang. "Real time facial feature localization based on improved active shape model." In 2012 5th International Congress on Image and Signal Processing (CISP). IEEE, 2012. http://dx.doi.org/10.1109/cisp.2012.6469713.

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Dang, Li, and Fanrang Kong. "Facial feature point extraction using a new improved Active Shape Model." In 2010 3rd International Congress on Image and Signal Processing (CISP). IEEE, 2010. http://dx.doi.org/10.1109/cisp.2010.5646914.

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Lifang Zhou, Bin Fang, Weisheng Li, and Peng Lai. "Improved active shape model for facial feature localization using poem descriptor." In 2013 International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR). IEEE, 2013. http://dx.doi.org/10.1109/icwapr.2013.6599314.

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Journal articles
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