Relevant bibliographies by topics / SURF FEATURES

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'SURF FEATURES'

Author: Grafiati
Published: 11 September 2023

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Journal articles on the topic "SURF FEATURES"

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Wang, Yin Tien, Chen Tung Chi, and Ying Chieh Feng. "Robot Simultaneous Localization and Mapping Using Speeded-Up Robust Features." Applied Mechanics and Materials 284-287 (January 2013): 2142–46. http://dx.doi.org/10.4028/www.scientific.net/amm.284-287.2142.

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An algorithm for robot mapping is proposed in this paper using the method of speeded-up robust features (SURF). Since SURFs are scale- and orientation-invariant features, they have higher repeatability than that of the features obtained by other detection methods. Even in the cases of using moving camera, the SURF method can robustly extract the features from image sequences. Therefore, SURFs are suitable to be utilized as the map features in visual simultaneous localization and mapping (SLAM). In this article, the procedures of detection and matching of the SURF method are modified to improve
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Wang, Yin-Tien, and Guan-Yu Lin. "Improvement of speeded-up robust features for robot visual simultaneous localization and mapping." Robotica 32, no. 4 (2013): 533–49. http://dx.doi.org/10.1017/s0263574713000830.

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SUMMARYA robot mapping procedure using a modified speeded-up robust feature (SURF) is proposed for building persistent maps with visual landmarks in robot simultaneous localization and mapping (SLAM). SURFs are scale-invariant features that automatically recover the scale and orientation of image features in different scenes. However, the SURF method is not originally designed for applications in dynamic environments. The repeatability of the detected SURFs will be reduced owing to the dynamic effect. This study investigated and modified SURF algorithms to improve robustness in representing vi
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Bay, Herbert, Andreas Ess, Tinne Tuytelaars, and Luc Van Gool. "Speeded-Up Robust Features (SURF)." Computer Vision and Image Understanding 110, no. 3 (2008): 346–59. http://dx.doi.org/10.1016/j.cviu.2007.09.014.

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Pandey, Ramesh Chand, Sanjay Kumar Singh, and K. K. Shukla. "Passive Copy- Move Forgery Detection Using Speed-Up Robust Features, Histogram Oriented Gradients and Scale Invariant Feature Transform." International Journal of System Dynamics Applications 4, no. 3 (2015): 70–89. http://dx.doi.org/10.4018/ijsda.2015070104.

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Copy-Move is one of the most common technique for digital image tampering or forgery. Copy-Move in an image might be done to duplicate something or to hide an undesirable region. In some cases where these images are used for important purposes such as evidence in court of law, it is important to verify their authenticity. In this paper the authors propose a novel method to detect single region Copy-Move Forgery Detection (CMFD) using Speed-Up Robust Features (SURF), Histogram Oriented Gradient (HOG), Scale Invariant Features Transform (SIFT), and hybrid features such as SURF-HOG and SIFT-HOG.
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.M, Suresha, and Sandeep. "Recognition of Birds in Blurred and Illumination Images by Local Features." International Journal of Advanced Research in Computer Science and Software Engineering 7, no. 7 (2017): 243. http://dx.doi.org/10.23956/ijarcsse/v7i7/0128.

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Local features are of great importance in computer vision. It performs feature detection and feature matching are two important tasks. In this paper concentrates on the problem of recognition of birds using local features. Investigation summarizes the local features SURF, FAST and HARRIS against blurred and illumination images. FAST and Harris corner algorithm have given less accuracy for blurred images. The SURF algorithm gives best result for blurred image because its identify strongest local features and time complexity is less and experimental demonstration shows that SURF algorithm is rob
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Shukla, Tuhin, Nishchol Mishra, and Sanjeev Sharma. "Automatic Image Annotation using SURF Features." International Journal of Computer Applications 68, no. 4 (2013): 17–24. http://dx.doi.org/10.5120/11567-6868.

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Tabuse, Masayoshi, Toshiki Kitaoka, and Dai Nakai. "Outdoor autonomous navigation using SURF features." Artificial Life and Robotics 16, no. 3 (2011): 356–60. http://dx.doi.org/10.1007/s10015-011-0950-8.

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Puyda, Volodymyr. "Surf Features Extraction in a Computer Vision System." Advances in Cyber-Physical Systems 2, no. 1 (2017): 29–31. http://dx.doi.org/10.23939/acps2017.01.029.

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Jhan, J. P., and J. Y. Rau. "A NORMALIZED SURF FOR MULTISPECTRAL IMAGE MATCHING AND BAND CO-REGISTRATION." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W13 (June 4, 2019): 393–99. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w13-393-2019.

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<p><strong>Abstract.</strong> Due to the raw images of multi-lens multispectral (MS) camera has significant misregistration errors, performing image registration for band co-registration is necessary. Image matching is an essential step for image registration, which obtains conjugate features on the overlapped areas, and use them to estimate the coefficients of a transformation model for correcting the geometrical errors. However, due to the none-linear intensity of spectral response, performing feature-based image matching (such as SURF) can only obtain only a few conjugate
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Jing Zhao, Jing Zhao. "Sports Motion Feature Extraction and Recognition Based on a Modified Histogram of Oriented Gradients with Speeded Up Robust Features." 電腦學刊 33, no. 1 (2022): 063–70. http://dx.doi.org/10.53106/199115992022023301007.

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<p>Traditional motion recognition methods can extract global features, but ignore the local features. And the obscured motion cannot be recognized. Therefore, this paper proposes a modified Histogram of oriented gradients (HOG) combining speeded up robust features (SURF) for sports motion feature extraction and recognition. This new method can fully extract the local and global features of the sports motion recognition. The new algorithm first adopts background subtraction to obtain the motion region. Direction controllable filter can effectively describe the motion edge features. The HO
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Dissertations / Theses on the topic "SURF FEATURES"

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Jurgensen, Sean M. "The rotated speeded-up robust features algorithm (R-SURF)." Thesis, Monterey, California: Naval Postgraduate School, 2014. http://hdl.handle.net/10945/42653.

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Approved for public release; distribution is unlimited<br>Includes supplemental materials<br>Weaknesses in the Fast Hessian detector utilized by the speeded-up robust features (SURF) algorithm are examined in this research. We evaluate the SURF algorithm to identify possible areas for improvement in the performance. A proposed alternative to the SURF detector is proposed called rotated SURF (R-SURF). This method utilizes filters that are rotated 45 degrees counter-clockwise, and this modification is tested with standard detector testing methods against the regular SURF detector. Performance te
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Brykt, Andreas. "A testbed for distributed detection ofkeypoints and extraction of descriptors forthe Speeded-Up-Robust-Features (SURF)algorithm." Thesis, KTH, Kommunikationsnät, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-141475.

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Detecting keypoints and computing descriptors needed in an imagerecognition algorithm are tasks that require substantial processing powerif they are to be executed in a short time span. If a network of sensornodes is used to capture the images to be processed, then the sensor nodescould be used to perform the actual processing. The system would dis-tribute the computing tasks to the available nodes in the network, so thatthe computing load can be divided among the nodes. By this, the com-puting time could possibly still be kept low, despite the large differencein available computing power betw
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Medeiros, Petr?cio Ricardo Tavares de. "Multifoveamento em multirresolu??o com f?veas m?veis." PROGRAMA DE P?S-GRADUA??O EM ENGENHARIA EL?TRICA E DE COMPUTA??O, 2016. https://repositorio.ufrn.br/jspui/handle/123456789/22258.

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Submitted by Automa??o e Estat?stica (sst@bczm.ufrn.br) on 2017-03-14T21:32:46Z No. of bitstreams: 1 PetrucioRicardoTavaresDeMedeiros_DISSERT.pdf: 5937912 bytes, checksum: c98c0e639d8348140e2635081d9744f4 (MD5)<br>Approved for entry into archive by Arlan Eloi Leite Silva (eloihistoriador@yahoo.com.br) on 2017-03-15T22:29:35Z (GMT) No. of bitstreams: 1 PetrucioRicardoTavaresDeMedeiros_DISSERT.pdf: 5937912 bytes, checksum: c98c0e639d8348140e2635081d9744f4 (MD5)<br>Made available in DSpace on 2017-03-15T22:29:35Z (GMT). No. of bitstreams: 1 PetrucioRicardoTavaresDeMedeiros_DISSERT.pdf: 593791
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Zavalina, Viktoriia. "Identifikace objektů v obraze." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2014. http://www.nusl.cz/ntk/nusl-220364.

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Master´s thesis deals with methods of objects detection in the image. It contains theoretical, practical and experimental parts. Theoretical part describes image representation, the preprocessing image methods, and methods of detection and identification of objects. The practical part contains a description of the created programs and algorithms which were used in the programs. Application was created in MATLAB. The application offers intuitive graphical user interface and three different methods for the detection and identification of objects in an image. The experimental part contains a test
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Saad, Elhusain Salem. "Defocus Blur-Invariant Scale-Space Feature Extractions." University of Dayton / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1418907974.

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Veľas, Martin. "Automatické třídění fotografií podle obsahu." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2013. http://www.nusl.cz/ntk/nusl-236399.

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This thesis deals with content based automatic photo categorization. The aim of the work is to experiment with advanced techniques of image represenatation and to create a classifier which is able to process large image dataset with sufficient accuracy and computation speed. A traditional solution based on using visual codebooks is enhanced by computing color features, soft assignment of visual words to extracted feature vectors, usage of image segmentation in process of visual codebook creation and dividing picture into cells. These cells are processed separately. Linear SVM classifier with e
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González, Valenzuela Ricardo Eugenio 1984. "Linear dimensionality reduction applied to SIFT and SURF feature descriptors." [s.n.], 2014. http://repositorio.unicamp.br/jspui/handle/REPOSIP/275499.

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Orientadores: Hélio Pedrini, William Robson Schwartz<br>Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Computação<br>Made available in DSpace on 2018-08-24T12:45:45Z (GMT). No. of bitstreams: 1 GonzalezValenzuela_RicardoEugenio_M.pdf: 22940228 bytes, checksum: 972bc5a0fac686d7eda4da043bbd61ab (MD5) Previous issue date: 2014<br>Resumo: Descritores locais robustos normalmente compõem-se de vetores de características de alta dimensionalidade para descrever atributos discriminativos em imagens. A alta dimensionalidade de um vetor de características implica custos consid
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Grünseisen, Vojtěch. "Vyhledávání graffiti tagů podle podobnosti." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2013. http://www.nusl.cz/ntk/nusl-236413.

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This work focuses on a possibility of using current computer vision alghoritms and methods for automatic similarity matching of so called graffiti tags. Those are such graffiti, that are used as a fast and simple signature of their authors. The process of development and implementation of CBIR system, which is created for this task, is described. For the purposes of finding images similarity, local features are used, most notably self-similarity features.
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Stefanik, Kevin Vincent. "Sequential Motion Estimation and Refinement for Applications of Real-time Reconstruction from Stereo Vision." Thesis, Virginia Tech, 2011. http://hdl.handle.net/10919/76802.

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This paper presents a new approach to the feature-matching problem for 3D reconstruction by taking advantage of GPS and IMU data, along with a prior calibrated stereo camera system. It is expected that pose estimates and calibration can be used to increase feature matching speed and accuracy. Given pose estimates of cameras and extracted features from images, the algorithm first enumerates feature matches based on stereo projection constraints in 2D and then backprojects them to 3D. Then, a grid search algorithm over potential camera poses is proposed to match the 3D features and find the larg
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Hubený, Marek. "Koncepty strojového učení pro kategorizaci objektů v obrazu." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2017. http://www.nusl.cz/ntk/nusl-316388.

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This work is focused on objects and scenes recognition using machine learning and computer vision tools. Before the solution of this problem has been studied basic phases of the machine learning concept and statistical models with accent on their division into discriminative and generative method. Further, the Bag-of-words method and its modification have been investigated and described. In the practical part of this work, the implementation of the Bag-of-words method with the SVM classifier was created in the Matlab environment and the model was tested on various sets of publicly available im
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Books on the topic "SURF FEATURES"

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Argentina) Ventana Sur (2019 (Buenos Aires. Ventana Sur 2019: Film guide. Instituto Nacional de Cine y Artes Audiovisuales. INCAA, 2019.

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Compassion focused therapy: Distinctive features. Routledge, 2010.

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Gilbert, Paul. Compassion focused therapy: Distinctive features. Routledge, 2010.

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Gagnon, François. Données sur l'économie du scénario au Québec pour le long métrage de fiction: Répertoire 1968-2000. Centre de recherche cinéma/réception de l'Université de Montréal, 2002.

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Canada. Feature Film Advisory Committee. The road to success : report of the Feature Film Advisory Committee =: La voie du succès : rapport du Comité consultatif sur le long métrage. Canadian Heritage = Patrimoine canadien, 1999.

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Williams, H. Major structural features of southeastern Canada and the Atlantic Continental Margin portrayed in regional gravity and magnetic maps =: Principaux éléments structuraux du sud-est du Canada et de la marge continentale de l'Atlantique tels que représentés sur des cartes gravimétriques et magnétiques régionales. Geological Survey of Canada = Commission géologique du Canada, 1994.

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Google Chrome Browser User Guide for Beginners and Seniors: Learn and Master How to Use Google Chrome Browser to Surf the Internet, Setup and Use All Modern Chrome Features from Basic to Advance. Independently Published, 2022.

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Crane, Rebecca. Mindfulness-Based Cognitive Therapy: Distinctive Features. Taylor & Francis Group, 2017.

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Mindfulness-Based Cognitive Therapy: Distinctive Features. Taylor & Francis Group, 2017.

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Crane, Rebecca. Mindfulness-Based Cognitive Therapy: Distinctive Features. Taylor & Francis Group, 2008.

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Book chapters on the topic "SURF FEATURES"

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Bay, Herbert, Tinne Tuytelaars, and Luc Van Gool. "SURF: Speeded Up Robust Features." In Computer Vision – ECCV 2006. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11744023_32.

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Souza, Luis, Christian Hook, João P. Papa, and Christoph Palm. "Barrett’s Esophagus Analysis Using SURF Features." In Informatik aktuell. Springer Berlin Heidelberg, 2017. http://dx.doi.org/10.1007/978-3-662-54345-0_34.

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Srinivas, Badrinath G., and Phalguni Gupta. "Palmprint Based Verification System Using SURF Features." In Communications in Computer and Information Science. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03547-0_24.

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Fu, Jing, Xiaojun Jing, Songlin Sun, Yueming Lu, and Ying Wang. "C-SURF: Colored Speeded Up Robust Features." In Trustworthy Computing and Services. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-35795-4_26.

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Shwetha, S., Sunanda Dixit, and B. I. Khondanpur. "Person Recognition Using Surf Features and Vola-Jones Algorithm." In Advances in Intelligent Systems and Computing. Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-3156-4_56.

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M’hiri, Faten, Claudia Chevrefils, and Jean-Philippe Sylvestre. "Quality Assessment of Retinal Hyperspectral Images Using SURF and Intensity Features." In Lecture Notes in Computer Science. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-66185-8_14.

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Zhang, Nan. "Computing Parallel Speeded-Up Robust Features (P-SURF) via POSIX Threads." In Emerging Intelligent Computing Technology and Applications. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04070-2_33.

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Pandey, Ramesh Chand, Rishabh Agrawal, Sanjay Kumar Singh, and K. K. Shukla. "Passive Copy Move Forgery Detection Using SURF, HOG and SIFT Features." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-11933-5_74.

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Batur, Aliya, Patigul Mamat, Wenjie Zhou, Yali Zhu, and Kurban Ubul. "Complex Printed Uyghur Document Image Retrieval Based on Modified SURF Features." In Pattern Recognition and Computer Vision. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-03338-5_9.

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Shah, Munir, Jeremiah Deng, and Brendon Woodford. "Illumination Invariant Background Model Using Mixture of Gaussians and SURF Features." In Computer Vision - ACCV 2012 Workshops. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-37410-4_27.

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Conference papers on the topic "SURF FEATURES"

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Du, Geng, Fei Su, and Anni Cai. "Face recognition using SURF features." In Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, edited by Mingyue Ding, Bir Bhanu, Friedrich M. Wahl, and Jonathan Roberts. SPIE, 2009. http://dx.doi.org/10.1117/12.832636.

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Ignat, Anca, and Ioan Păvăloi. "Occluded Iris Recognition using SURF Features." In 16th International Conference on Computer Vision Theory and Applications. SCITEPRESS - Science and Technology Publications, 2021. http://dx.doi.org/10.5220/0010255405080515.

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Deshmukh, Jyoti, and Udhav Bhosle. "SURF features based classifiers for mammogram classification." In 2017 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET). IEEE, 2017. http://dx.doi.org/10.1109/wispnet.2017.8299734.

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Lv, Di, Yunfu Deng, Zhihao Li, et al. "Advanced SURF Features Based Flexible Object Detection." In 2019 IEEE International Conference on Robotics and Biomimetics (ROBIO). IEEE, 2019. http://dx.doi.org/10.1109/robio49542.2019.8961377.

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Pancham, Ardhisha, Daniel Withey, and Glen Bright. "Tracking image features with PCA-SURF descriptors." In 2015 14th IAPR International Conference on Machine Vision Applications (MVA). IEEE, 2015. http://dx.doi.org/10.1109/mva.2015.7153206.

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Rabbani, Golam Shams, Sharmin Sultana, Md Nazmul Hasan, Salem Quddus Fahad, and Jia Uddin. "Person identification using SURF features of dental radiograph." In the 3rd International Conference. ACM Press, 2019. http://dx.doi.org/10.1145/3309074.3309115.

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Karthik, R., A. AnnisFathima, and V. Vaidehi. "Panoramic view creation using invariant momentsand SURF features." In 2013 Third International Conference on Recent Trends in Information Technology (ICRTIT). IEEE, 2013. http://dx.doi.org/10.1109/icrtit.2013.6844233.

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Gigaud, Guillaume, and Pierre Moulin. "Traitor-tracing aided by compressed SURF image features." In 2010 44th Annual Conference on Information Sciences and Systems (CISS). IEEE, 2010. http://dx.doi.org/10.1109/ciss.2010.5464707.

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Alfadhli, Fares Hasan Obaid, Ali Afzalian Mand, Md Shohel Sayeed, Kok Swee Sim, and Mundher Al-Shabi. "Classification of tuberculosis with SURF spatial pyramid features." In 2017 International Conference on Robotics, Automation and Sciences (ICORAS). IEEE, 2017. http://dx.doi.org/10.1109/icoras.2017.8308044.

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Cui, Kai, Hua Cai, Yao Zhang, and Huan Chen. "A face alignment method based on SURF features." In 2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI). IEEE, 2017. http://dx.doi.org/10.1109/cisp-bmei.2017.8301964.

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Reports on the topic "SURF FEATURES"

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Michaels, Michelle, Theodore Letcher, Sandra LeGrand, Nicholas Webb, and Justin Putnam. Implementation of an albedo-based drag partition into the WRF-Chem v4.1 AFWA dust emission module. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/42782.

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Employing numerical prediction models can be a powerful tool for forecasting air quality and visibility hazards related to dust events. However, these numerical models are sensitive to surface conditions. Roughness features (e.g., rocks, vegetation, furrows, etc.) that shelter or attenuate wind flow over the soil surface affect the magnitude and spatial distribution of dust emission. To aide in simulating the emission phase of dust transport, we used a previously published albedo-based drag partition parameterization to better represent the component of wind friction speed affecting the immedi
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LeGrand, Sandra, Theodore Letcher, Gregory Okin, et al. Application of a satellite-retrieved sheltering parameterization (v1.0) for dust event simulation with WRF-Chem v4.1. Engineer Research and Development Center (U.S.), 2023. http://dx.doi.org/10.21079/11681/47116.

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Employing numerical prediction models can be a powerful tool for forecasting air quality and visibility hazards related to dust events. However, these numerical models are sensitive to surface conditions. Roughness features (e.g., rocks, vegetation, furrows, etc.) that shelter or attenuate wind flow over the soil surface affect the magnitude and spatial distribution of dust emission. To aide in simulating the emission phase of dust transport, we used a previously published albedo-based drag partition parameterization to better represent the component of wind friction speed affecting the immedi
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Babenko, Oksana. Ідеї екуменізму в публіцистиці митрополита Андрея Шептицького: сучасне прочитання. Ivan Franko National University of Lviv, 2023. http://dx.doi.org/10.30970/vjo.2023.52-53.11717.

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Subject of the article’s study – ecumenism of Metropolitan Andrei Sheptytskyi and reflection of this phenomenon in the works of scientists and modern Ukrainian media. Main objective of the study: analyze what Ukrainian scientists, journalists and different media are writing about Sheptytkyi’s ecumenism. Methodology: We used a bibliographic method to accumulate factual material, a qualitative content analysis to isolate the ideas of ecumenism from the journalism of Metropolitan Andrey Sheptytskyi, a cultural-historical method that made it possible to consider the ideas of ecumenism in the conte
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