Multi-View Stereo 3D Challenge
Can you develop the Multi-View Stereo (MVS) 3D mapping algorithm for commercial satellite imagery with the best accuracy and completeness? The 3D Mapping Challenge in July 2016 invites Solvers from around the world to generate an algorithm to convert high-resolution satellite images to 3D point clouds. Participants will join a global community working to benchmark research and foster innovation of 3D point clouds through crowdsourcing.
Who We Are: The Intelligence Advanced Research Projects Activity (IARPA) focuses on high-risk, high-payoff research. The Multi-View Stereo 3D challenge is related to our CORE3D program, which works to fully automated methods for timely 3D model creation leveraging spectral, textural, and dimensional information from satellite data to yield models that are dimensionally true and accurate.
What We’re Doing: The Multi-View Stereo 3D Mapping Challenge, which launches on 11 July 2016, is being offered by IARPA, within the Office of the Director of National Intelligence (ODNI). Numerous commercial satellites, including newly emerging CubeSats, cover large areas with higher revisit rates and deliver high-quality imagery in near real-time to customers. Although the entire earth has been, and continues to be, imaged multiple times, fully automated data analysis remains limited. The Multi-View Stereo 3D Mapping Challenge is the first concerted effort to invite experts from across government, academia, industry and solver communities to derive accurate 3D point clouds from multi-view satellite imagery that will advance imagery technology and potentially foster enormous humanitarian impact. Solvers will be provided commercial imagery data files over a large area and asked to generate and submit 3D point clouds.
Where We’re Doing This: Around the world—anyone over age 18 is welcome to participate. We’re looking for solutions from anyone who thinks they might have a way of addressing this problem, including data scientists, 3D modelers, geospatial analysts, computer programmers, and even experts in disciplines we haven’t yet considered.
When We’re Doing This: The challenge will be broken out into two stages, the introductory Explorer Challenge and the iterative Master Challenge. Participants will be given the full satellite data sets at the beginning of Explorer that will remain the same during the Master challenge. During the Explorer Challenge, a single region within the data set will be assigned and evaluated against. During the Master Challenge, additional regions will be added to the challenge. Solvers will be able to continue to work on their algorithm during the break between the Explorer Challenge and Master Challenge. Additionally, there will be a Best Paper Challenge during the Master Challenge open to any solver to submit the best write-up of their approach to the algorithm creation.
|When does registration begin?||July 2016|
|Where to learn more about the challenge, including rules, criteria and
|Where do solvers register?||http://crowdsourcing.topcoder.com/iarpa_3dchallenge|
|What is the duration of Explorer Challenge?||July 11 - August 2016|
|What is the duration of Master Challenge?||September 2016|
|When is the Best Paper Contest?||September 2016|
Why We’re Doing This: IARPA is conducting this challenge to invite the broader research community of industry and academia, with or without experience in multi-view satellite imagery, to participate in a convenient, efficient and non-contractual way. IARPA’s use of a crowdsourcing approach to stimulate breakthroughs in science and technology also supports the White House’s Strategy for American Innovation, as well as government transparency and efficiency. The goals and objectives of the Challenge are to:
- Promote and benchmark research in multiple view stereo algorithms applied to satellite imagery
- Stimulate various communities to develop and enhance automated methods to derive accurate 3D point clouds from multi-view satellite imagery, including computer vision, remote sensing and photogrammetry
- Foster innovation through crowdsourcing and moving beyond current research limitations for 3D point clouds
- Cultivate and sustain an ongoing collaborative community dedicated to this technology and research
Why Participate? Throughout the challenge, an online leaderboard will display solvers’ rankings and accomplishments, giving them various opportunities to have their work viewed and appreciated by stakeholders from industry, government and academic communities. Solvers will be eligible to win cash prizes during the Explorer and Master challenges from a total prize purse of over $100K. Winners will be invited to present their solutions at a conference hosted by IARPA in the Fall, where they will detail their approach. Excellent paper submissions will also be eligible for cash prizes.
For more information, see the press release.