Visual identification of biological motion for underwater human-robot interaction.
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| Title: | Visual identification of biological motion for underwater human-robot interaction. |
|---|---|
| Authors: | Sattar, Junaed1 junaed@umn.edu, Dudek, Gregory2 dudek@cim.mcgill.ca |
| Source: | Autonomous Robots. Jan2018, Vol. 42 Issue 1, p111-124. 14p. |
| Subjects: | Robotics in oceanography, Human-robot interaction, Tracking & trailing, Sensor arrays, Remote sensing |
| Abstract: | We present an algorithm for underwater robots to visually detect and track human motion. Our objective is to enable human-robot interaction by allowing a robot to follow behind a human moving in (up to) six degrees of freedom. In particular, we have developed a system to allow a robot to detect, track and follow a scuba diver by using frequency-domain detection of biological motion patterns. The motion of biological entities is characterized by combinations of periodic motions which are inherently distinctive. This is especially true of human swimmers. By using the frequency-space response of spatial signals over a number of video frames, we attempt to identify signatures pertaining to biological motion. This technique is applied to track scuba divers in underwater domains, typically with the robot swimming behind the diver. The algorithm is able to detect a range of motions, which includes motion directly away from or towards the camera. Once detected, the motion of the diver relative to the vehicle is then tracked using an Unscented Kalman Filter, an approach for non-linear estimation. The efficiency of our approach makes it attractive for real-time applications on-board our underwater vehicle, and in future applications we intend to track scuba divers in real-time with the robot. The paper presents an algorithmic overview of our approach, together with experimental evaluation based on underwater video footage. [ABSTRACT FROM AUTHOR] |
| Copyright of Autonomous Robots is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 127147552 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Visual identification of biological motion for underwater human-robot interaction. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Sattar%2C+Junaed%22">Sattar, Junaed</searchLink><relatesTo>1</relatesTo><i> junaed@umn.edu</i><br /><searchLink fieldCode="AR" term="%22Dudek%2C+Gregory%22">Dudek, Gregory</searchLink><relatesTo>2</relatesTo><i> dudek@cim.mcgill.ca</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Autonomous+Robots%22">Autonomous Robots</searchLink>. Jan2018, Vol. 42 Issue 1, p111-124. 14p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Robotics+in+oceanography%22">Robotics in oceanography</searchLink><br /><searchLink fieldCode="DE" term="%22Human-robot+interaction%22">Human-robot interaction</searchLink><br /><searchLink fieldCode="DE" term="%22Tracking+%26+trailing%22">Tracking & trailing</searchLink><br /><searchLink fieldCode="DE" term="%22Sensor+arrays%22">Sensor arrays</searchLink><br /><searchLink fieldCode="DE" term="%22Remote+sensing%22">Remote sensing</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: We present an algorithm for underwater robots to visually detect and track human motion. Our objective is to enable human-robot interaction by allowing a robot to follow behind a human moving in (up to) six degrees of freedom. In particular, we have developed a system to allow a robot to detect, track and follow a scuba diver by using frequency-domain detection of biological motion patterns. The motion of biological entities is characterized by combinations of periodic motions which are inherently distinctive. This is especially true of human swimmers. By using the frequency-space response of spatial signals over a number of video frames, we attempt to identify signatures pertaining to biological motion. This technique is applied to track scuba divers in underwater domains, typically with the robot swimming behind the diver. The algorithm is able to detect a range of motions, which includes motion directly away from or towards the camera. Once detected, the motion of the diver relative to the vehicle is then tracked using an Unscented Kalman Filter, an approach for non-linear estimation. The efficiency of our approach makes it attractive for real-time applications on-board our underwater vehicle, and in future applications we intend to track scuba divers in real-time with the robot. The paper presents an algorithmic overview of our approach, together with experimental evaluation based on underwater video footage. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Autonomous Robots is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s10514-017-9644-y Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 14 StartPage: 111 Subjects: – SubjectFull: Robotics in oceanography Type: general – SubjectFull: Human-robot interaction Type: general – SubjectFull: Tracking & trailing Type: general – SubjectFull: Sensor arrays Type: general – SubjectFull: Remote sensing Type: general Titles: – TitleFull: Visual identification of biological motion for underwater human-robot interaction. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Sattar, Junaed – PersonEntity: Name: NameFull: Dudek, Gregory IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Text: Jan2018 Type: published Y: 2018 Identifiers: – Type: issn-print Value: 09295593 Numbering: – Type: volume Value: 42 – Type: issue Value: 1 Titles: – TitleFull: Autonomous Robots Type: main |
| ResultId | 1 |
