{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/geometry-based-region-proposals-for-real-time","title":"Geometry-Based Region Proposals for Real-Time Robot Detection of Tabletop Objects","arxiv_id":"1703.04665","date":"2017-03-14","proceeding":null,"authors":["Alexander Broad","Brenna Argall"],"abstract":"We present a novel object detection pipeline for localization and recognition\nin three dimensional environments. Our approach makes use of an RGB-D sensor\nand combines state-of-the-art techniques from the robotics and computer vision\ncommunities to create a robust, real-time detection system. We focus\nspecifically on solving the object detection problem for tabletop scenes, a\ncommon environment for assistive manipulators. Our detection pipeline locates\nobjects in a point cloud representation of the scene. These clusters are\nsubsequently used to compute a bounding box around each object in the RGB\nspace. Each defined patch is then fed into a Convolutional Neural Network (CNN)\nfor object recognition. We also demonstrate that our region proposal method can\nbe used to develop novel datasets that are both large and diverse enough to\ntrain deep learning models, and easy enough to collect that end-users can\ndevelop their own datasets. Lastly, we validate the resulting system through an\nextensive analysis of the accuracy and run-time of the full pipeline.","url_abs":"http://arxiv.org/abs/1703.04665v1","url_pdf":"http://arxiv.org/pdf/1703.04665v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"geometry-based-region-proposals-for-real-time","repo_url":"https://github.com/asbroad/geom_rcnn","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"tf","reach":null}],"tasks":[{"task_slug":"novel-object-detection","task_name":"Novel Object Detection"},{"task_slug":"object","task_name":"Object"},{"task_slug":"object-detection","task_name":"Object Detection"},{"task_slug":"object-recognition","task_name":"Object Recognition"},{"task_slug":"region-proposal","task_name":"Region Proposal"},{"task_slug":"object-detection-1","task_name":"object-detection"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}