9783731511014.pdf
Visual perception is one of the most important sources of information for both humans and robots. A particular challenge is the acquisition and interpretation of complex unstructured scenes. This work contributes to active vision for humanoid robots. A semantic model of the scene is created, which i...
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KIT Scientific Publishing
2022
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Διαθέσιμο Online: | https://doi.org/10.5445/KSP/1000132320 |
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oapen-20.500.12657-529482022-02-19T02:52:04Z Active Vision for Scene Understanding Grotz, Markus Roboter Humanoide Robotik robots Robots humanoid robots bic Book Industry Communication::U Computing & information technology::UY Computer science::UYA Mathematical theory of computation::UYAM Maths for computer scientists Visual perception is one of the most important sources of information for both humans and robots. A particular challenge is the acquisition and interpretation of complex unstructured scenes. This work contributes to active vision for humanoid robots. A semantic model of the scene is created, which is extended by successively changing the robot's view in order to explore interaction possibilities of the scene. 2022-02-18T15:02:36Z 2022-02-18T15:02:36Z 2021 book ONIX_20220218_9783731511014_9 2512-0875 9783731511014 https://library.oapen.org/handle/20.500.12657/52948 eng Karlsruhe Series on Humanoid Robotics application/pdf n/a 9783731511014.pdf https://doi.org/10.5445/KSP/1000132320 KIT Scientific Publishing KIT Scientific Publishing 10.5445/KSP/1000132320 10.5445/KSP/1000132320 44e29711-8d53-496b-85cc-3d10c9469be9 9783731511014 KIT Scientific Publishing 7 204 Karlsruhe open access |
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English |
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Visual perception is one of the most important sources of information for both humans and robots. A particular challenge is the acquisition and interpretation of complex unstructured scenes. This work contributes to active vision for humanoid robots. A semantic model of the scene is created, which is extended by successively changing the robot's view in order to explore interaction possibilities of the scene. |
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KIT Scientific Publishing |
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2022 |
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https://doi.org/10.5445/KSP/1000132320 |
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