Academic literature on the topic 'Active stereo vision'
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Journal articles on the topic "Active stereo vision"
Grosso, E., and M. Tistarelli. "Active/dynamic stereo vision." IEEE Transactions on Pattern Analysis and Machine Intelligence 17, no. 9 (1995): 868–79. http://dx.doi.org/10.1109/34.406652.
Full textJang, Mingyu, Hyunse Yoon, Seongmin Lee, Jiwoo Kang, and Sanghoon Lee. "A Comparison and Evaluation of Stereo Matching on Active Stereo Images." Sensors 22, no. 9 (April 26, 2022): 3332. http://dx.doi.org/10.3390/s22093332.
Full textGasteratos, Antonios. "Tele-Autonomous Active Stereo-Vision Head." International Journal of Optomechatronics 2, no. 2 (June 13, 2008): 144–61. http://dx.doi.org/10.1080/15599610802081753.
Full textYexin Wang, Yexin Wang, Fuqiang Zhou Fuqiang Zhou, and Yi Cui Yi Cui. "Single-camera active stereo vision system using fiber bundles." Chinese Optics Letters 12, no. 10 (2014): 101301–4. http://dx.doi.org/10.3788/col201412.101301.
Full textSamson, Eric, Denis Laurendeau, Marc Parizeau, Sylvain Comtois, Jean-François Allan, and Clément Gosselin. "The Agile Stereo Pair for active vision." Machine Vision and Applications 17, no. 1 (February 23, 2006): 32–50. http://dx.doi.org/10.1007/s00138-006-0013-7.
Full textFeller, Michael, Jae-Sang Hyun, and Song Zhang. "Active Stereo Vision for Precise Autonomous Vehicle Control." Electronic Imaging 2020, no. 16 (January 26, 2020): 258–1. http://dx.doi.org/10.2352/issn.2470-1173.2020.16.avm-257.
Full textKo, Jung-Hwan. "Active Object Tracking System based on Stereo Vision." Journal of the Institute of Electronics and Information Engineers 53, no. 4 (April 25, 2016): 159–66. http://dx.doi.org/10.5573/ieie.2016.53.4.159.
Full textPorta, J. M., J. J. Verbeek, and B. J. A. Kröse. "Active Appearance-Based Robot Localization Using Stereo Vision." Autonomous Robots 18, no. 1 (January 2005): 59–80. http://dx.doi.org/10.1023/b:auro.0000047287.00119.b6.
Full textYongchang Wang, Kai Liu, Qi Hao, Xianwang Wang, D. L. Lau, and L. G. Hassebrook. "Robust Active Stereo Vision Using Kullback-Leibler Divergence." IEEE Transactions on Pattern Analysis and Machine Intelligence 34, no. 3 (March 2012): 548–63. http://dx.doi.org/10.1109/tpami.2011.162.
Full textMohamed, Abdulla, Phil F. Culverhouse, Ricardo De Azambuja, Angelo Cangelosi, and Chenguang Yang. "Automating Active Stereo Vision Calibration Process with Cobots." IFAC-PapersOnLine 50, no. 2 (December 2017): 163–68. http://dx.doi.org/10.1016/j.ifacol.2017.12.030.
Full textDissertations / Theses on the topic "Active stereo vision"
Li, Fuxing. "Active stereo for AGV navigation." Thesis, University of Oxford, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.338984.
Full textFung, Chun Him. "A biomimetic active stereo head with torsional control /." View abstract or full-text, 2006. http://library.ust.hk/cgi/db/thesis.pl?ECED%202006%20FUNG.
Full textWong, Yuk Lam. "Optical tracking for medical diagnosis based on active stereo vision /." View abstract or full-text, 2006. http://library.ust.hk/cgi/db/thesis.pl?ELEC%202006%20WONGY.
Full textChan, Balwin Man Hong. "A miniaturized 3-D endoscopic system using active stereo-vision /." View Abstract or Full-Text, 2002. http://library.ust.hk/cgi/db/thesis.pl?ELEC%202002%20CHANB.
Full textIncludes bibliographical references (leaves 106-108). Also available in electronic version. Access restricted to campus users.
Kihlström, Helena. "Active Stereo Reconstruction using Deep Learning." Thesis, Linköpings universitet, Institutionen för medicinsk teknik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-158276.
Full textUrquhart, Colin W. "The active stereo probe : the design and implementation of an active videometrics system." Thesis, University of Glasgow, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.312498.
Full textBjörkman, Mårten. "Real-Time Motion and Stereo Cues for Active Visual Observers." Doctoral thesis, KTH, Numerical Analysis and Computer Science, NADA, 2002. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-3382.
Full textUlusoy, Ilkay. "Active Stereo Vision: Depth Perception For Navigation, Environmental Map Formation And Object Recognition." Phd thesis, METU, 2003. http://etd.lib.metu.edu.tr/upload/12604737/index.pdf.
Full texts internal parameters bring high computational load. Thus, finding the strategy to be followed in a simulated world and then applying this on real robot for real applications is preferable. In this study, we describe an algorithm for object recognition and cognitive map formation using stereo image data in a 3D virtual world where 3D objects and a robot with active stereo imaging system are simulated. Stereo imaging system is simulated so that the actual human visual system properties are parameterized. Only the stereo images obtained from this world are supplied to the virtual robot. By applying our disparity algorithm, depth map for the current stereo view is extracted. Using the depth information for the current view, a cognitive map of the environment is updated gradually while the virtual agent is exploring the environment. The agent explores its environment in an intelligent way using the current view and environmental map information obtained up to date. Also, during exploration if a new object is observed, the robot turns around it, obtains stereo images from different directions and extracts the model of the object in 3D. Using the available set of possible objects, it recognizes the object.
Huster, Andrew Christian. "Design and Validation of an Active Stereo Vision System for the OSU EcoCAR 3." The Ohio State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=osu1499251870670736.
Full textMohammadi, Vahid. "Design, Development and Evaluation of a System for the Detection of Aerial Parts and Measurement of Growth Indices of Bell Pepper Plant Based on Stereo and Multispectral Imaging." Electronic Thesis or Diss., Bourgogne Franche-Comté, 2022. http://www.theses.fr/2022UBFCK109.
Full textDuring the growth of plants, monitoring them brings much benefits to the producers. This monitoring includes the measurement of physical properties, counting plants leaves, detection of plants and separation of them from weeds. All these can be done different techniques, however, the techniques are favorable that are non-destructive because plant is a very sensitive creature that any manipulation can put disorder in its growth or lead to losing leaves or branches. Imaging techniques are of the best solutions for plants growth monitoring and geometric measurements. In this regard, in this project the use of stereo imaging and multispectral data was studied. Active and passive stereo imaging were employed for the estimation of physical properties and counting leaves and multispectral data was utilized for the separation of crop and weed. Bell pepper plant was used for imaging measurements for a period of 30 days and for crop/weed separation, the spectral responses of bell pepper and five weeds were measured. Nine physical properties of pepper leaves (i.e. main leaf diameters, leaf area, leaf perimeter etc.) were measured using a scanner and was used as a database and also for comparing the estimated values to the actual values. The stereo system consisted of two LogiTech cameras and a video projector. First the stereo system was calibrated using sample images of a standard checkerboard in different position and angles. The system was controlled using the computer for turning a light line on, recording videos of both cameras while light is being swept on the plant and then stopping the light. The frames were extracted and processed. The processing algorithm first filtered the images for removing noise and then thresholded the unwanted pixels of environment. Then, using the peak detection method of Center of Mass the main and central part of the light line was extracted. After, the images were rectified by using the calibration information. Then the correspondent pixels were detected and used for the 3D model development. The obtained point cloud was transformed to a meshed surface and used for physical properties measurement. Passive stereo imaging was used for leaf detection and counting. For passive stereo matching six different matching algorithms and three cost functions were used and compared. For spectral responses of plants, they were freshly moved to the laboratory, leaves were detached from the plants and placed on a blur dark background. Type A lights were used for illumination and the spectral measurements were carried out using a spectroradiometer from 380 nm to 1000 nm. To reduce the dimensionality of the data, PCA and wavelet transform were used. Results of this study showed that the use of stereo imaging can propose a cheap and non-destructive tool for agriculture. An important advantage of active stereo imaging is that it is light-independent and can be used during the night. However, the use of active stereo for the primary stage of growth provides acceptable results but after that stage, the system will be unable to detect and reconstruct all leaves and plant's parts. Using ASI the R2 values of 0.978 and 0.967 were obtained for the estimation leaf area and perimeter, respectively. The results of separation of crop and weeds using spectral data were very promising and the classifier—which was based on deep learning—could completely separate pepper from other five weeds
Books on the topic "Active stereo vision"
Active computer vision by cooperative focus and stereo. New York: Springer-Verlag, 1989.
Find full textKrotkov, Eric Paul. Active Computer Vision by Cooperative Focus and Stereo. New York, NY: Springer New York, 1989. http://dx.doi.org/10.1007/978-1-4613-9663-5.
Full textKrotkov, Eric Paul. Active Computer Vision by Cooperative Focus and Stereo. New York, NY: Springer New York, 1989.
Find full textTakao, Kumazawa, Kruger Lawrence, and Mizumura Kazue, eds. The polymodal receptor: A gateway to pathological pain. Amsterdam: Elsevier, 1996.
Find full textJohansen, Bruce, and Adebowale Akande, eds. Nationalism: Past as Prologue. Nova Science Publishers, Inc., 2021. http://dx.doi.org/10.52305/aief3847.
Full text(Editor), T. Kumazawa, L. Kruger (Editor), and K. Mizumura (Editor), eds. The Polymodal Receptor - A Gateway to Pathological Pain (Progress in Brain Research). Elsevier Science, 1996.
Find full textBook chapters on the topic "Active stereo vision"
Hogue, Andrew, and Michael Jenkin. "Active Stereo Vision." In Computer Vision, 1–6. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-03243-2_282-1.
Full textHogue, Andrew, and Michael R. M. Jenkin. "Active Stereo Vision." In Computer Vision, 8–12. Boston, MA: Springer US, 2014. http://dx.doi.org/10.1007/978-0-387-31439-6_282.
Full textHogue, Andrew, and Michael Jenkin. "Active Stereo Vision." In Computer Vision, 27–32. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-63416-2_282.
Full textWang, Ce, Zhanyi Hu, and Song De Ma. "Active vision based stereo vision." In Recent Developments in Computer Vision, 229–39. Berlin, Heidelberg: Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/3-540-60793-5_78.
Full textGrosso, Enrico, Massimo Tistarelli, and Giulio Sandini. "Active/dynamic stereo for navigation." In Computer Vision — ECCV'92, 516–25. Berlin, Heidelberg: Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/3-540-55426-2_57.
Full textIkeuchi, Katsushi, Yasuyuki Matsushita, Ryusuke Sagawa, Hiroshi Kawasaki, Yasuhiro Mukaigawa, Ryo Furukawa, and Daisuke Miyazaki. "Photometric Stereo." In Active Lighting and Its Application for Computer Vision, 107–23. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-56577-0_5.
Full textSkifstad, Kurt, and Ramesh Jain. "A New Paradigm for Computational Stereo." In Active Perception and Robot Vision, 465–79. Berlin, Heidelberg: Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/978-3-642-77225-2_24.
Full textKrotkov, Eric Paul. "Stereo with Verging Cameras." In Active Computer Vision by Cooperative Focus and Stereo, 43–62. New York, NY: Springer New York, 1989. http://dx.doi.org/10.1007/978-1-4613-9663-5_4.
Full textKrotkov, Eric Paul. "An Agile Stereo Camera System." In Active Computer Vision by Cooperative Focus and Stereo, 7–18. New York, NY: Springer New York, 1989. http://dx.doi.org/10.1007/978-1-4613-9663-5_2.
Full textKawasaki, Hiroshi, Yutaka Ohsawa, Ryo Furukawa, and Yasuaki Nakamura. "Dense 3D Reconstruction with an Uncalibrated Active Stereo System." In Computer Vision – ACCV 2006, 882–91. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11612704_88.
Full textConference papers on the topic "Active stereo vision"
Urquhart, C. W., J. P. Siebert, J. P. McDonald, and R. J. Fryer. "Active Animate Stereo Vision." In British Machine Vision Conference 1993. British Machine Vision Association, 1993. http://dx.doi.org/10.5244/c.7.8.
Full textJenkin and Tsotsos. "Active stereo vision and cyclotorsion." In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition. IEEE Comput. Soc. Press, 1994. http://dx.doi.org/10.1109/cvpr.1994.323903.
Full textViitanen, Jouko O. "Active stereo for mobile robot vision." In Photonics East (ISAM, VVDC, IEMB), edited by David P. Casasent. SPIE, 1998. http://dx.doi.org/10.1117/12.325795.
Full textMedioni, Gérard, and Jean-Luc Jezouin. "An Implementation of an Active Stereo Range Finder1." In Machine Vision. Washington, D.C.: Optica Publishing Group, 1987. http://dx.doi.org/10.1364/mv.1987.tha3.
Full textSumanasena, M. G. B., J. G. Samarawickrama, and A. A. Pasqual. "Mobile Stereo Camera Platform for Active Vision." In 2006 International Conference on Industrial and Information Systems. IEEE, 2006. http://dx.doi.org/10.1109/iciinfs.2006.347164.
Full textAntonisse, Hendrick J. "Active stereo vision routines using PRISM-3." In Applications in Optical Science and Engineering, edited by David P. Casasent. SPIE, 1992. http://dx.doi.org/10.1117/12.131578.
Full textClark, James J., Michael J. Weisman, and Alan L. Yuille. "Using viewpoint consistency in active stereo vision." In Applications in Optical Science and Engineering, edited by David P. Casasent. SPIE, 1992. http://dx.doi.org/10.1117/12.131573.
Full textSumanasena, M. G. B., J. G. Samarawickrama, and A. A. Pasqual. "Mobile Stereo Camera Platform for Active Vision." In First International Conference on Industrial and Information Systems. IEEE, 2006. http://dx.doi.org/10.1109/iciis.2006.365738.
Full textBartolomei, Luca, Matteo Poggi, Fabio Tosi, Andrea Conti, and Stefano Mattoccia. "Active Stereo Without Pattern Projector." In 2023 IEEE/CVF International Conference on Computer Vision (ICCV). IEEE, 2023. http://dx.doi.org/10.1109/iccv51070.2023.01693.
Full textSiebert, J. P., C. W. Urquhart, D. F. Wilson, J. P. McDonald, P. H. Mowforth, and R. J. Fryer. "The Active Stereo Probe: Dynamic Video Feedback." In British Machine Vision Conference 1991. Springer-Verlag London Limited, 1991. http://dx.doi.org/10.5244/c.5.56.
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