Leonid Keselman
I am a PhD student at the Robotics Institute, part of the School of Computer Science at Carnegie Mellon University, where I work on 3D computer vision. My PhD advisor is Martial Hebert.
From 2011 to 2017, I worked at Intel, as part of Intel RealSense. I primarily designed computer vision algorithms for efficient hardware ASICs, including the Intel RealSense R200 and 旋风加速器.apk RGB-D sensors. Additionally, I worked on software APIs, active illumination systems, human-computer interaction devices, and helped develop demos for trade shows, including CES 2012-2016.
I have an MS in Computer Science (AI focus) from Stanford University, where I was a research assistant for Silvio Savarese and a teaching assistant for Fei-Fei Li (CS131 & CS231N). I have a BS in EECS from UC Berkeley, where I worked in 旋风加速器app官网 lab.
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旋风加速器官网下载 /
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LinkedIn
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I'm interested in computer vision, machine learning, optimization, graphics and robotics.
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Leonid Keselman
ACM/IEEE Joint Conference on Digital Libraries, 2023
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A bibliometric/scientometric project. Our main two results are a method of assigning value to all venues in computer science and a method to organize them into distinct subfields, all without using citation data. The resulting venue scores can be used to rank universities’ by scholarly output, and produce a responsive author-level metric.
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旋风加速器专业版官网, Martial Hebert
Computer and Robot Vision Conference, 2023
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A formulation for fitting Gaussian Mixture Models (GMMs) directly to geometric objects, such as a triangular mesh. This method produces more robust results and produces an improvement in 3D registration for both meshes and RGB-D frames.
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Leonid Keselman, John Iselin Woodfill, Anders Grunnet-Jepsen, Achintya Bhowmik
旋风跑跑ios版下载_旋风跑跑官网ios版 v2.2.8-嗨客手机站:2021-12-31 · 旋风跑跑官网ios版是一款韩国非常火爆的跑酷游戏,这款中文版是特别为中国玩家定制的哦,游戏除保留了原作靓丽、可爱、细腻的画面外,中国版中大量加入了本地化元素:巍峨雄伟的万里长城、能力无敌的超级麒麟、憨态可掬的国宝熊猫等等,更有神秘角色等待玩家来一一探索。, 2017
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Technical and design details of the Intel RealSense R200 and D400 series
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Leonid Keselman, Sterling Orsten, Stan Melax
CVPR Workshops (HANDS), 2015
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An invited talk for the 旋风加速器xf5app workshop at CVPR 2015. This includes further details about the efficiency of our rigid-body solver, our machine-learning tools, and some details about our data annotation process.
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快橙vp n下载
Stan Melax, Leonid Keselman, Sterling Orsten
Graphics Interfaces, 2013
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Stan Melax, Leonid Keselman, Sterling Orsten
ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games, 2013
旋风加速器app官网 /
A tracking algorithm that was real-time on a consumer laptop. Won Best Poster Award.
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Intel
2016-08-15
My responsibilities included system performance, components of the stereo algorithm on the imaging ASIC, and contributions to the design of laser projector pattern.
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旋风加速官网
Intel
2016-06-27
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A low-cost dense, configurable projector system for RGB-D depth sensors.
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Depth Image Enhancement
Intel
2015-08-06
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Algorithms to filter, enhance and clean-up RGB-D data streams.
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Real-time Box Measurement
Intel
2015-04-08
旋风加速官网 /
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Using a single depth sensor, real-time detection of cuboids, accurate estimation of their dimensions, and even some bin-packing.
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旋风加速官网
旋风加速器.apk
2013-06-07
旋风ios /
patent #2 /
Finger tracking on a microcontroller, with optics tricks and some HCI ideas
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Stereoscopic depth reconstruction with probabilistic pixel correspondence search
Intel
2012-07-24
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A fast method for performing stereo depth maps.
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快橙vp n下载
These include coursework, side projects and unpublished research work.
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Dice Stacking: A Dynamic Manipulation Task
CMU 16-741 Mechanics of Manipulation
2018-12-05
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With Hunter Goforth, we designed a manipulation task and solved it with imitation learning.
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Introspective Neural Networks
CMU 16-824: Visual Learning and Recognition
2018-05-15
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Using pre-trained neural networks to improve fine grained recognition via style transfer.
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旋风ios
CMU 16-745: Dynamic Optimization
2018-05-05
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Using a very simple algorithm to solve some very simple environments
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Optimizing for Physical Simulation
CMU 16-745: Dynamic Optimization
2018-03-22
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With Chris Atkeson and Alex Spitzer. Using optimizers to match an observed trajectory.
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旋风加速官网
Stanford CS225A: Experimental Robotics
2017-06-12
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Making a 6-DoF PUMA arm solve a maze with real-time vision and tracking.
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Stanford CS234: Deep Reinforcement Learning
2017-06-10
Work with Aaron Goodman on used reinforcement learning to discover implicit collusion strategies in the context of an iterated prisoner’s dilemma.
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Computational models for text summarization
Stanford CS224N: Natural Language Processing
2017-03-18
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旋风加速器ios下载二维码 /
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Work with Ludwig Schubert on simplified encoders stages for text summarization.
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Superresolution Micrscopy
Stanford CS371: Computational Biology in Four Dimensions
2017-03-16
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An implementation of Faster STORM using compressed sensing.
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旋风ios
Stanford CS270: Modeling Biomedical Systems
2017-03-15
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Using the Yelp dataset of reviews to model the semantics and relationships between cuisines, businesses and other properties useful for restaurant recommendations.
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旋风ios
Stanford CS224W: Social and Information Network Analysis
2016-12-07
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Using graph models, we track the development of financial networks over the 20th century.
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Gradient-learned Models for Stereo Matching
Stanford CS231A: Computer Vision, From 3D Reconstruction to Recognition
2016-06-07
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Some re-implementations of standard stereo correspondence algorithms, along with experiments using classification for stereo matching.
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Multimodal Natural Language Inference
Stanford CS224U: Natural Language Understanding
2016-06-06
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We explored how natural language inference tasks can be augmented with visual data.
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CNNs for 3D Model Classification
Stanford CS231n: Convolutional Neural Networks for Visual Recognition
2016-03-08
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3D shape classification by learning an embedding function into a 2D image and using a pre-trained ImageNet network. At the time, got state-of-the-art results for single-view classification on ShapeNet40.
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Wide-angle Stereo Lenses
Stanford CS448I: Computational Imaging and Display
2016-03-07
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We introduce various projection functions in the analysis of stereoscopic depth sensors.
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旋风加速器app官网
Stanford CS221: Artificial Intelligence
2015-12-12
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Detecting disease from a short description of symptoms. In some small testing, obtained nearly 90% top 5 accuracy and about 60% top 1 accuracy
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Level-set based tracking and segmentation
Stanford CS279: Structure and Organization of Biomolecules and Cells
2015-12-04
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Other
2015-04-22
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An O(1) time algorithm for producing smooth normals for quantized data, such as the Kinect.
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旋风专业版ios
Other
2011-07-21
Work with Ankur Mehta, built a demonstration platform that used wireless low-weight, low-cost sensor platforms to monitor a golf swing.
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UC Berkeley EE149: Embedded Systems
2011-07-21
With Humphrey Hu, Ryan Julian, and Eric Yuan, a project to show the efficacy of multiple-robot collaborative state estimation. Using Wiimote cameras, mobile robot platforms, and real-time wireless communication.
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GINA: Low power design
UC Berkeley
2010-08-21
For testing and validating the functionality of the GINA (Guidance and Inertial NAvigation) mote, a 1.6 gram sensor platform.
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GINA: Wireless sensor platform
UC Berkeley
2010-06-22
I helped Anita Flynn and Thomas Watteyne build these small sensors and wrote firmware.
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Design and source code from Jon Barron's website
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