Lee, H., Wicke, M., Kusy, B., Gnawali, O., Guibas, L. Persistence-based Segmentation of Deformable Shapes, 3rd Workshop on Non-Rigid Shape Analysis and Deformable Image Alignment. CAP Profile. --Gordon Bell, Senior Researcher, Microsoft Corporation "This book provides both an insightful overview of the emerging field of wireless sensor networks, and an in depth treatment of algorithmic signal and information processing issues. Cortial, J., Farhat, C., Guibas, L. J., Rajashekhar, M. FaceNet: Tracking people and acquiring canonical face images in a wireless camera sensor network, Object tracking in the presence of occlusions via a camera network. He received the ACM Allen Newell Award. Leonidas J. Guibas, Department of Computer Science, Stanford University, His research centers on algorithms for sensing, modeling, reasoning, rendering, and acting on the physical world. Wireless Sensor Networks: An Information Processing Approach: Amazon.de: Feng Zhao, Leonidas Guibas: Fremdsprachige Bücher We discuss how the package design was influenced by various considerations, including extensibility, support for multiple kinetic data structures, access to existing data structures and algorithms in CGAL, as well as debugging. Use features like bookmarks, note taking and highlighting while reading Wireless Sensor Networks: An Information Processing Approach (ISSN). Project Management. Heath, K., Gelfand, N., Ovsjanikov, M., Aanjaneya, M., Guibas, L. J. Meshless Shape and Motion Design for Multiple Deformable Objects. Discover Book Depository's huge selection of Leonidas Guibas books online. Ground-breaking research shaped the Computational Geometry field.


Most frequent co-Author Most cited colleague Top subject. Yang, D., Shin, J., Ercan, A., Guibas, L. Collaborative signal and information processing: An information-directed approach. Such transient states are typically of low population in simulation samples. Leonidas J. Guibas, Department of Computer Science, Stanford University, His research centers on algorithms for sensing, modeling, reasoning, rendering, and acting on the physical world. In this paper we present a package for implementing exact kinetic data structures built on objects which move along polynomial trajectories. Our deformable spanner succinctly encodes all proximity information in a deforming point cloud, giving us efficient kinetic algorithms for problems such as the closest pair, the near neighbors of all points, approximate nearest neighbor search (aka approximate Voronoi diagram), well-separated pair decompositions, and approximate k-centers. Chaudhuri, S., Kalogerakis, E., Guibas, L., Koltun, V. Exploration of Continuous Variability in Collections of 3D Shapes. His main subsequent employers were Xerox PARC, MIT, and DEC/SRC. Kim, Y. M., Mitra, N. J., Yan, D., Guibas, L. Microtiles: Extracting Building Blocks from Correspondences. Complex fracture patterns of interacting and branching cracks are handled using a small set of topological operations for splitting, merging, and terminating crack fronts. Locating and bypassing routing holes in sensor networks. Dr. Richard Keiser. However, the solvent information in molecular simulations are often ignored in current methods, because of the large number of solvent molecules in a system and the indistinguishability of solvent molecules upon their exchange.We present a solvent signature that compactly summarizes the solvent distribution in the high-dimensional data, and then define a distance metric between different configurations using this signature. Wand, M., Jenke, P., Huang, Q., Bokeloh, M., Guibas, L., Schilling, A. Mitra, Niloy, J., Floery, S., Ovsjanikov, M., Gelfand, N., Guibas, L., Pottmann, H. Compressed sensing and time-parallel reduced-order modeling for structural health monitoring using a DDDAS. Clark Center Faculty. In: Computer Graphics Forum 34(5) (Proc. Learning Generalizable Final-State Dynamics of 3D Rigid Objects, Davis Rempe, Srinath Sridhar, He Wang, and Leonidas J. Guibas, CVPR Workshop on 3D Scene Understanding for Vision, Graphics, and Robotics, … Uploaded by. Despite their simple structure, there is some debate over whether they fold in a two-state or multi-state manner. We present a novel reconstruction algorithm that, given an input point set sampled from an object S, builds a one-parameter family of complexes that approximate S at different scales. A Concise and Provably Informative Multi-Scale Signature Based on Heat Diffusion, Topological methods for exploring low-density states in biomolecular folding pathways. VTU Important Syllabus - Free download as (.rtf), PDF File (.pdf), Text File (.txt) or read online for free. Distributed Team Leader. Leonidas John Guibas (Greek: Λεωνίδας Γκίμπας) is the Paul Pigott Professor of Computer Science and Electrical Engineering at Stanford University, where he heads the geometric computation group and is a member of the computer graphics and artificial intelligence laboratories. Free delivery worldwide on over 20 million titles. Chen, D., Driemel, A., Guibas, L., Nguyen, A., Wenk, C. Ovsjanikov, M., Merigot, Q., Patraucean, V., Guibas, L. Consistent Shape Maps via Semidefinite Programming, Dirichlet Energy for Analysis and Synthesis of Soft Maps, Map-Based Exploration of Intrinsic Shape Differences and Variability. Chazal, F., Cohen-Steiner, D., Glisse, M., Guibas, L., J., Oudot, S., Y. ShapeGoogle: a computer vision approach for invariant shape retrieval. View details for DOI 10.1093/bioinformatics/btm250, View details for Web of Science ID 000249248300006, View details for DOI 10.1145/1239451.1239514, View details for Web of Science ID 000248914000066, View details for DOI 10.1145/1239451.1239499, View details for Web of Science ID 000248914000051, View details for DOI 10.1016/j.comgeo.2006.05.008, View details for Web of Science ID 000245339400005, View details for Web of Science ID 000247855100021, View details for Web of Science ID 000247062800153, View details for Web of Science ID 000254383500016, View details for Web of Science ID 000251798600053, View details for Web of Science ID 000249117701016, View details for DOI 10.1016/j.cagd.2006.03.002, View details for Web of Science ID 000239260900005. Uncertainty and Variability in Point Cloud Surface Data. In this paper, we develop a computational approach to explore the relatively low populated transition or intermediate states in biomolecular folding pathways, based on a topological data analysis tool, MAPPER, with simulation data from large-scale distributed computing. Free delivery worldwide on over 20 million titles. A Computational Framework for Handling Motion. VTU Syllabus Random Important questions The models provided for the algebraic kernel support both exact operations and inexact approximations with heuristics to improve numerical stability. One Point Isometric Matching with the Heat Kernel. Uploaded by. He has been at Stanford since 1984 as Professor of Computer Science. Wireless Sensor Networks: An Information Processing Approach (ISSN) - Kindle edition by Zhao, Feng, Guibas, Leonidas. Leonidas John Guibas (Greek: Λεωνίδας Γκίμπας) is the Paul Pigott Professor of Computer Science and Electrical Engineering at Stanford University, where he heads the geometric computation group and is a member of the computer graphics and artificial intelligence laboratories. Ganzes Profil ansehen. A successful application of this method is given on a motivating example, a RNA hairpin with GCAA tetraloop, where we are able to provide structural evidence from computer simulations on the multiple intermediate states and exhibit different pictures about unfolding and refolding pathways. Adams, B., Wicke, M., Ovsjanikov, M., Wand, M., Seidel, H., Guibas, L. J. 100–108. Chen, C., Su, H., Huang, Q., Zhang, L., Guibas, L. Guided Real-Time Scanning of Indoor Environments, Computer Graphics Forum. Zhao and Guibas begin with the canonical problem of localizing and tracking moving objects, then systematically examine the many fundamental sensor network issues that spring from it, including network discovery, service establishment, data routing and aggregation, query processing, programming models, and system organization. Das von Zi Ye und seinem Mentor Prof. Tim Hoffmann zusammen mit Olga Diamanti, Chengcheng Tang und Leonidas Guibas in Stanford verfasste Paper ist in der Zeitschrift "Computer Graphics Forum" erschienen.

Professor Guibas heads the Geometric Computation group in the Computer Science Department of Stanford University … The edges in the spanner pick out important proximities in the structure, labeling a small number of atom pairs or backbone region pairs as being of primary interest. Localization of Mobile Users Using Trajectory Matching. Leonidas John Guibas (Greek: Λεωνίδας Γκίμπας) is the Paul Pigott Professor of Computer Science and Electrical Engineering at Stanford University, where he heads the geometric computation group and is a member of the computer graphics and artificial intelligence laboratories. Huang, Q., Adams, B., Wicke, M., Guibas, L. J. Mitra, Niloy, J., Guibas, L., Giesen, J., Pauly, M. The Identity Management Problem — A Short Survey. Supervised Earth Mover's Distance Learning and its Computer Vision Applications, Joint Shape Segmentation with Linear Programming, A Condition Number for Non-Rigid Shape Matching, An Optimization Approach to Improving Collections of Shape Maps. Our fragment libraries, which offer a wide range of optimal fragments suited to different accuracies of fit, may prove to be useful for generating better decoy sets for ab initio protein folding and for generating accurate loop conformations in homology modeling. Boissonnat, J., Guibas, L. J., Oudot, S. Y. We next incorporate the solvent information into the construction of Markov state models and present a fast geometric clustering algorithm which combines both the solute-based and solvent-based distances.We have tested our method on several different molecular dynamical systems, including alanine dipeptide, carbon nanotube, and benzene rings. Guibas interests span computational geometry, geometric modeling, computer graphics, computer vision, sensor networks, robotics, and discrete algorithms --- all areas in which he has published and lectured extensively. Hairpins are a ubiquitous secondary structure motif in RNA molecules. The company’s technical advisory board includes former Google, Uber, and Apple visionaries Brian McClendon and Jaron Waldman, as well as Dr. Leonidas Guibas, a prominent Stanford University professor, and Herman Kaess, former CEO of Bosch Korea. Professor Guibas heads the Geometric Computation group in the Computer Science Department of Stanford University and is a member of the Computer Graphics and Artificial Intelligence Laboratories. Scrum Master. For a set S of points in ℝ(d), an s-spanner is a subgraph of the complete graph with node set S such that any pair of points is connected via some path in the spanner whose total length is at most s times the Euclidean distance between the points. Caleb Chiam, Gokul Dharan, Alvin Hou, Anthea Li, Yew Siang Tang, Kaichun Mo, Davis Rempe, Mikaela Angelina Uy, From Planes to Corners: Multi-Purpose Primitive Detection in Unorganized 3D Point Clouds. Chen, D., Guibas, L. J., Hershberger, J., Sun, J. Dr. The research contributions Guibas is known for include finger trees, red-black trees, fractional cascading, the Guibas–Stolfi algorithm for Delaunay triangulation, an optimal data structure for point location, the quad-edge data structure for representing planar subdivisions, Metropolis light transport, and kinetic data structures for keeping track of objects in motion. As a first step towards addressing this problem, an algorithm has been developed using an approximation of the medial axis to simplify an electron-density isosurface. Agarwal, P., K., Berg, M., De, Gao, J., Guibas, Leonidas, J., Har-Peled, S. Pauly, M., Mitra, N., J., Giesen, J., Gross, M., Guibas, L. Carlsson, G., Zomorodian, A., Collins, A., Guibas, L. GLIDER: Gradient Landmark-Based Distributed Routing for sensor networks. ACM recognizes excellence through its eminent awards for technical and professional achievements and contributions in computer science and information technology. Towards a dynamic data driven system for structural and material health monitoring. Scrum Product Owner. Yichen Li. We predict that a tightly coordinated process of hemifusion neck expansion and pore formation is responsible for the rapid vesicle fusion mechanism, while isolated enlargement of the hemifusion diaphragm leads to the formation of a metastable hemifused intermediate. Leonidas Guibas is the Paul Pigott Professor of Computer Science (and by courtesy, Electrical Engineering) at Stanford University, where he heads the Geometric Computation group. We find that the accuracy depends on the complexity and varies from 2.9A for a 2.7-state model on the basis of fragments of length 7-0.76A for a 15-state model on the basis of fragments of length 5. Kolodny, R., Guibas, L., Levitt, M., Koehl, P. Exploring protein folding trajectories using geometric spanners, Staying in the Middle: Exact and Approximate Medians in R1 and R2 for Moving Points. The methods we described should also be broadly applicable to a wide range of biomolecular simulation analyses. Yang, D. B., Gonzalez-Banos, H. H., Guibas, L. J. Foundations of Statistics. Zhao and Guibas begin with the canonical problem of localizing and tracking moving objects, then systematically examine the many fundamental sensor network issues that spring from it, including network discovery, service establishment, data routing and aggregation, query processing, programming models, and system organization. Motskin, A., Downes, I., Kusy, B., Gnawali, O., Guibas, L. Overcomplete Radon Bases for Target Property Management in Sensor Networks. On the basis of these simulations, we have identified a number of intermediates that are consistent with experimental results. Kalojanov, J., Bokeloh, M., Wand, M., Guibas, L., Seidel, H., Slusallek, P. Functional Maps: A Flexible Representation of Maps Between Shapes. View details for DOI 10.1016/j.comgeo.2005.10.001, View details for Web of Science ID 000238302900002, View details for PubMedCentralID PMC3001688, View details for Web of Science ID 000239817400012, View details for DOI 10.1007/s11036-006-4471-y, View details for Web of Science ID 000237835400007, View details for Web of Science ID 000239567900010, View details for Web of Science ID 000238417300061, View details for Web of Science ID 000238978000013, View details for Web of Science ID 000239426200024, View details for Web of Science ID 000259418000030, View details for DOI 10.1007/s00453-005-1153-2, View details for Web of Science ID 000232830600003. Robust Voronoi-based Curvature and Feature Estimation, Dynamic Resource Management and Matching in Sensor Networks. I received my B.S. He works on algorithms for sensing, modeling, reasoning, rendering, and acting on the physical world. Russel, D., Karavelas, M. I., Guibas, L. J. Yao, Y., Sun, J., Huang, X., Bowman, G. R., Singh, G., Lesnick, M., Guibas, L. J., Pande, V. S., Carlsson, G. Efficient Reconstruction of Nonrigid Shape and Motion from Real-Time 3D Scanner Data. Lin, H., Lu, M., Milosavljevic, N., Gao, J., Guibas, Leonidas, J. MULTI-PERSON TRACKING FROM SPARSE 3D TRAJECTORIES IN A CAMERA SENSOR NETWORK, Robust Extraction of 1D Skeletons from Grayscale 3D Images. We present a new meshless animation framework for elastic and plastic materials that fracture. Ovsjanikov, M., Merigot, Q., Memoli, F., Guibas, L. On Discrete Killing Vector Fields and Patterns on Surfaces. Kaichun Mo, Shilin Zhu, Angel X. Chang, Li Yi, Subarna Tripathi, Leonidas J. Guibas, Hao Su: PartNet: A Large-scale Benchmark for Fine-grained and Hierarchical Part … Joint Embedding of 3D Scan and CAD Objects. Fast and free shipping free returns cash on delivery available on eligible purchase. Characterization of transient intermediate or transition states is crucial for the description of biomolecular folding pathways, which is, however, difficult in both experiments and computer simulations. Leonidas Leo Guibas - Paul Pigott Professor in the School of Engineering and Professor of Computer Science and (by courtesy) of Electrical Engineering . These models are built from short timescale simulations and then propagated to extract long timescale dynamics. Ercan, A. O., Yang, D. B., El Gamal, A., Guibas, L. J. Landmark-based information storage and retrieval in sensor networks, Efficient collision detection among moving spheres with unknown trajectories, Automated crystallographic ligand building using the medial axis transform of an electron-density isosurface. Guided Real-Time Scanning of Indoor Environments, Graph Matching with Anchor Nodes: A Learning Approach, Acquiring 3D Indoor Environments with Variability and Repetition. Discover Book Depository's huge selection of Leonidas Guibas books online. Energy efficient intrusion detection in camera sensor networks, Sparse Data Aggregation in Sensor Networks. Han Liu, Ulysse Vimont, Michael Wand, Marie-Paule Cani, Stefanie Hahmann, Damien Rohmer, Niloy J. Mitra: Schumitsch, B., Thrun, S., Guibas, L., Olukotun, K. Camera network node selection for target localization in the presence of occlusions. Andy Nguyen, A., Ben-Chen, M., Welnicka, K., Ye, Y., Guibas, L. As-Killing-As-Possible Vector Fields for Planar Deformation. In this paper we propose a new sparse (1 + ε)-spanner with O(n/ε(d)) edges, where ε is a specified parameter. aggregation algorithms assume Bayesian belief broadcast Chapter clock cluster-head communication component computation cost covariance defined Delaunay … View details for Web of Science ID 000230169100004, View details for Web of Science ID 000231441000031, View details for Web of Science ID 000231323800048, View details for Web of Science ID 000230452800023, View details for DOI 10.1109/JSAC.2004.837364, View details for Web of Science ID 000226063100016, View details for Web of Science ID 000230375000004, View details for DOI 10.1016/j.cag.2004.08.015, View details for Web of Science ID 000225055200008, View details for Web of Science ID 000225807500008, View details for Web of Science ID 000224315900003, View details for DOI 10.1016/j.comgeo.2004.03.008, View details for Web of Science ID 000221974900005, View details for Web of Science ID 000222055900036, View details for Web of Science ID 000223848100226, View details for Web of Science ID 000222055900018, View details for Web of Science ID 000222055900031, View details for DOI 10.1109/JPROC.2003.814921, View details for Web of Science ID 000184655000006, View details for DOI 10.1007/s00454-003-2925-6, View details for Web of Science ID 000183405700005, View details for Web of Science ID 000180994200102, View details for Web of Science ID 000189435400008, View details for Web of Science ID 000186833000017.