{"id":20620591,"url":"https://github.com/lcav/surface-reconstruction","last_synced_at":"2026-04-20T11:31:41.367Z","repository":{"id":37027437,"uuid":"81346359","full_name":"LCAV/surface-reconstruction","owner":"LCAV","description":"Code for papers 'Sampling at unknown locations: Uniqueness and reconstruction under constraints' and 'Sampling at unknown locations, with an application in surface retrieval'","archived":false,"fork":false,"pushed_at":"2023-02-10T23:08:18.000Z","size":1826,"stargazers_count":2,"open_issues_count":4,"forks_count":0,"subscribers_count":8,"default_branch":"master","last_synced_at":"2025-03-06T20:16:39.151Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/LCAV.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2017-02-08T15:50:09.000Z","updated_at":"2022-05-04T03:03:28.000Z","dependencies_parsed_at":"2025-01-17T05:11:19.537Z","dependency_job_id":"0a1381d9-21c2-43ed-b7b6-d14f89c3e4d5","html_url":"https://github.com/LCAV/surface-reconstruction","commit_stats":null,"previous_names":[],"tags_count":1,"template":false,"template_full_name":null,"purl":"pkg:github/LCAV/surface-reconstruction","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/LCAV%2Fsurface-reconstruction","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/LCAV%2Fsurface-reconstruction/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/LCAV%2Fsurface-reconstruction/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/LCAV%2Fsurface-reconstruction/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/LCAV","download_url":"https://codeload.github.com/LCAV/surface-reconstruction/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/LCAV%2Fsurface-reconstruction/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":32045172,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-20T10:33:29.490Z","status":"ssl_error","status_checked_at":"2026-04-20T10:32:30.107Z","response_time":94,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.6:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-11-16T12:14:56.277Z","updated_at":"2026-04-20T11:31:41.349Z","avatar_url":"https://github.com/LCAV.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"\n# Sampling at unknown locations: Uniqueness and reconstruction under constraints\n\nThis repository contains all the code to reproduce the \nresults of the paper\n**Sampling at unknown locations: Uniqueness and reconstruction under \nconstraints**\n by G. Elhami, M. Pacholska, A. Scholefield, B. Bejar and M. Vetterli.\n\nThe part of the code related to polynomials with rational warping builds on top \nof the code for paper\n**Sampling at Unknown Locations**, by M. Pacholska, A. Scholefield, B. Bejar and \nM. Vetterli.\n\nCode that generated the figures form the previous paper can be found under fist \nversion `v1.0`\n\n## Abstract\n\nTraditional sampling results assume that the sample locations are known. \nMotivated by simultaneous localization and mapping (SLAM) and structure from \nmotion (SfM), we investigate sampling at unknown locations. Without further \nconstraints, the problem is often hopeless. For example, we recently showed \nthat, for polynomial and bandlimited signals, it is possible to find two \nsignals, arbitrarily far from each other, that fit the measurements. However, we \nalso showed that this can be overcome by adding constraints to the sample \npositions.\n\nIn this paper, we show that these constraints lead to a uniform sampling of \na composite of functions. Furthermore, the formulation retains the key aspects \nof the SLAM and SfM problems, whilst providing uniqueness, in many cases.\n\nWe demonstrate this by studying two simple examples of constrained sampling \nat unknown locations. In the first, we consider sampling a periodic bandlimited \nsignal composite with an unknown linear function. We derive the sampling \nrequirements for uniqueness and present an algorithm that recovers both the \nbandlimited signal and the linear warping. Furthermore, we prove that, when the \nrequirements for uniqueness are not met, the cases of multiple solutions have \nmeasure zero.\n\nFor our second example, we consider polynomials sampled such that the \nsampling positions are constrained by a rational function. We previously proved \nthat, if a specific sampling requirement is met, uniqueness is achieved. In \naddition, we present an alternate minimization scheme for solving the resulting \nnon-convex optimization problem.\n\nFinally, simulation results are provided to support our theoretical \nanalysis.\n\n## Authors\n\nMichalina Pacholska, EPFL\n\nGolnoosh Elhami, EPFL\n\n\u003cimg \nsrc=\"http://lcav.epfl.ch/files/content/sites/lcav/files/images/Home/LCAV_anim_200.gif\"\u003e\n\n\n#### Contact\n\nMichalina Pacholska, michalina.pacholska at epfl.ch\n\nGolnoosh Elhami, golnoosh.elhami at epfl.ch\n\n## About\n\n### Polynomial simulations\nIn order to recreate figures used in the paper related to polynomial based simulations,\none has to first run:\n\n    python surface-tests.py\n    \nor, in the python console:\n\n    `exec(open(\"surface-tests.py\").read())`\n   \nNote that this script takes several hours to run on four Intel i7 cores.\nAfter data generation all figures can be generated by Jupyter Notebook `generate_figures.ipynb`.\n\nIf you want to just have a preview how the code works, you can use Notebook `examples.ipynb`.\nThis notebook contains an example how to use ALS solver and how to use the whole pipeline \n(with few tests, which compute fast). \n\n### Unwarping simulations\nIn order to recreate figures used in the paper related to unwarping of periodic bandlimitted simulations,\none has to first run:\n\n    python simulate_alpha_equal_2pi_over_2Kplus1.py\n    python simulate_alpha_less_than_alpha_c.py\n    python simulate_alpha_less_than_pi_over_K.py\n    python simulate_alpha_more_than_pi_over_K.py\n    python simulate_change_b.py\n    \nNote that these scripts take several hours to run. The simulation results are however, saved in folder `unwarping_simulation_results/`.\nAfter data generation all figures can be generated by Jupyter Notebook `generate_figures_unwarping.ipynb`.\n\n## Requirements\n\nThis project uses Python 3. It requires:\n\n    scipy\n    matblotlib\n    jupyter\n    sortedcontainers\n   \nYou can install all of them by running:\n\n    pip install -r requirements.txt\n    \nor in the `conda` environment:\n\n    conda install --file requirements.txt\n    \nSpecific version of all packages used are in the file `all_requirements.txt`,\nwhich can also be used with `pip` and `conda`. \n\n\n## License\n\n```\nCopyright (c) 2018, Michalina Pacholska\n\nPermission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the \"Software\"), to deal\nin the Software without restriction, including without limitation the rights\nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell\ncopies of the Software, and to permit persons to whom the Software is\nfurnished to do so, subject to the following conditions:\n\nThe above copyright notice and this permission notice shall be included in all\ncopies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\nSOFTWARE.\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flcav%2Fsurface-reconstruction","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Flcav%2Fsurface-reconstruction","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flcav%2Fsurface-reconstruction/lists"}