{"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/real-time-dense-stereo-matching-with-elas-on","title":"Real-Time Dense Stereo Matching With ELAS on FPGA Accelerated Embedded Devices","arxiv_id":"1802.07210","date":"2018-02-20","proceeding":null,"authors":["Oscar Rahnama","Duncan Frost","Ondrej Miksik","Philip H. S. Torr"],"abstract":"For many applications in low-power real-time robotics, stereo cameras are the\nsensors of choice for depth perception as they are typically cheaper and more\nversatile than their active counterparts. Their biggest drawback, however, is\nthat they do not directly sense depth maps; instead, these must be estimated\nthrough data-intensive processes. Therefore, appropriate algorithm selection\nplays an important role in achieving the desired performance characteristics.\n  Motivated by applications in space and mobile robotics, we implement and\nevaluate a FPGA-accelerated adaptation of the ELAS algorithm. Despite offering\none of the best trade-offs between efficiency and accuracy, ELAS has only been\nshown to run at 1.5-3 fps on a high-end CPU. Our system preserves all\nintriguing properties of the original algorithm, such as the slanted plane\npriors, but can achieve a frame rate of 47fps whilst consuming under 4W of\npower. Unlike previous FPGA based designs, we take advantage of both components\non the CPU/FPGA System-on-Chip to showcase the strategy necessary to accelerate\nmore complex and computationally diverse algorithms for such low power,\nreal-time systems.","url_abs":"http://arxiv.org/abs/1802.07210v1","url_pdf":"http://arxiv.org/pdf/1802.07210v1.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":"real-time-dense-stereo-matching-with-elas-on","repo_url":"https://github.com/torrvision/ELAS_SoC","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":null,"task_name":"CPU"},{"task_slug":"stereo-matching-1","task_name":"Stereo Matching"},{"task_slug":"stereo-matching","task_name":"Stereo Matching Hand"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}