Parallel Architectures and Parallel Algorithms for Integrated Vision Systems:
Computer vision is one of the most complex and computationally intensive problem. Like any other computationally intensive problems, parallel pro cessing has been suggested as an approach to solving the problems in com puter vision. Computer vision employs algorithms from a wide range of areas suc...
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Boston, MA
Springer US
1990
|
| Schriftenreihe: | The Kluwer International Series in Engineering and Computer Science, Robotics: Vision, Manipulation and Sensors
108 |
| Schlagworte: | |
| Online-Zugang: | BTU01 URL des Erstveröffentlichers |
| Zusammenfassung: | Computer vision is one of the most complex and computationally intensive problem. Like any other computationally intensive problems, parallel pro cessing has been suggested as an approach to solving the problems in com puter vision. Computer vision employs algorithms from a wide range of areas such as image and signal processing, advanced mathematics, graph theory, databases and artificial intelligence. Hence, not only are the comput ing requirements for solving vision problems tremendous but they also demand computers that are efficient to solve problems exhibiting vastly dif ferent characteristics. With recent advances in VLSI design technology, Single Instruction Multiple Data (SIMD) massively parallel computers have been proposed and built. However, such architectures have been shown to be useful for solving a very limited subset of the problems in vision. Specifically, algorithms from low level vision that involve computations closely mimicking the architec ture and require simple control and computations are suitable for massively parallel SIMD computers. An Integrated Vision System (IVS) involves com putations from low to high level vision to be executed in a systematic fashion and repeatedly. The interaction between computations and information dependent nature of the computations suggests that architectural require ments for computer vision systems can not be satisfied by massively parallel SIMD computers |
| Beschreibung: | 1 Online-Ressource (XVIII, 158 p) |
| ISBN: | 9781461315391 |
| DOI: | 10.1007/978-1-4613-1539-1 |
Internformat
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| 520 | |a Computer vision is one of the most complex and computationally intensive problem. Like any other computationally intensive problems, parallel pro cessing has been suggested as an approach to solving the problems in com puter vision. Computer vision employs algorithms from a wide range of areas such as image and signal processing, advanced mathematics, graph theory, databases and artificial intelligence. Hence, not only are the comput ing requirements for solving vision problems tremendous but they also demand computers that are efficient to solve problems exhibiting vastly dif ferent characteristics. With recent advances in VLSI design technology, Single Instruction Multiple Data (SIMD) massively parallel computers have been proposed and built. However, such architectures have been shown to be useful for solving a very limited subset of the problems in vision. Specifically, algorithms from low level vision that involve computations closely mimicking the architec ture and require simple control and computations are suitable for massively parallel SIMD computers. An Integrated Vision System (IVS) involves com putations from low to high level vision to be executed in a systematic fashion and repeatedly. The interaction between computations and information dependent nature of the computations suggests that architectural require ments for computer vision systems can not be satisfied by massively parallel SIMD computers | ||
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| discipline | Informatik |
| doi_str_mv | 10.1007/978-1-4613-1539-1 |
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| id | DE-604.BV045187184 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T08:10:59Z |
| institution | BVB |
| isbn | 9781461315391 |
| language | English |
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| physical | 1 Online-Ressource (XVIII, 158 p) |
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| publishDate | 1990 |
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| record_format | marc |
| series2 | The Kluwer International Series in Engineering and Computer Science, Robotics: Vision, Manipulation and Sensors |
| spelling | Choudhary, Alok N. Verfasser aut Parallel Architectures and Parallel Algorithms for Integrated Vision Systems by Alok N. Choudhary, Janak H. Patel Boston, MA Springer US 1990 1 Online-Ressource (XVIII, 158 p) txt rdacontent c rdamedia cr rdacarrier The Kluwer International Series in Engineering and Computer Science, Robotics: Vision, Manipulation and Sensors 108 Computer vision is one of the most complex and computationally intensive problem. Like any other computationally intensive problems, parallel pro cessing has been suggested as an approach to solving the problems in com puter vision. Computer vision employs algorithms from a wide range of areas such as image and signal processing, advanced mathematics, graph theory, databases and artificial intelligence. Hence, not only are the comput ing requirements for solving vision problems tremendous but they also demand computers that are efficient to solve problems exhibiting vastly dif ferent characteristics. With recent advances in VLSI design technology, Single Instruction Multiple Data (SIMD) massively parallel computers have been proposed and built. However, such architectures have been shown to be useful for solving a very limited subset of the problems in vision. Specifically, algorithms from low level vision that involve computations closely mimicking the architec ture and require simple control and computations are suitable for massively parallel SIMD computers. An Integrated Vision System (IVS) involves com putations from low to high level vision to be executed in a systematic fashion and repeatedly. The interaction between computations and information dependent nature of the computations suggests that architectural require ments for computer vision systems can not be satisfied by massively parallel SIMD computers Computer Science Computer Imaging, Vision, Pattern Recognition and Graphics Processor Architectures Control, Robotics, Mechatronics Artificial Intelligence (incl. Robotics) Computer science Microprocessors Artificial intelligence Computer graphics Control engineering Robotics Mechatronics Patel, Janak H. aut Erscheint auch als Druck-Ausgabe 9781461288251 https://doi.org/10.1007/978-1-4613-1539-1 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Choudhary, Alok N. Patel, Janak H. Parallel Architectures and Parallel Algorithms for Integrated Vision Systems Computer Science Computer Imaging, Vision, Pattern Recognition and Graphics Processor Architectures Control, Robotics, Mechatronics Artificial Intelligence (incl. Robotics) Computer science Microprocessors Artificial intelligence Computer graphics Control engineering Robotics Mechatronics |
| title | Parallel Architectures and Parallel Algorithms for Integrated Vision Systems |
| title_auth | Parallel Architectures and Parallel Algorithms for Integrated Vision Systems |
| title_exact_search | Parallel Architectures and Parallel Algorithms for Integrated Vision Systems |
| title_full | Parallel Architectures and Parallel Algorithms for Integrated Vision Systems by Alok N. Choudhary, Janak H. Patel |
| title_fullStr | Parallel Architectures and Parallel Algorithms for Integrated Vision Systems by Alok N. Choudhary, Janak H. Patel |
| title_full_unstemmed | Parallel Architectures and Parallel Algorithms for Integrated Vision Systems by Alok N. Choudhary, Janak H. Patel |
| title_short | Parallel Architectures and Parallel Algorithms for Integrated Vision Systems |
| title_sort | parallel architectures and parallel algorithms for integrated vision systems |
| topic | Computer Science Computer Imaging, Vision, Pattern Recognition and Graphics Processor Architectures Control, Robotics, Mechatronics Artificial Intelligence (incl. Robotics) Computer science Microprocessors Artificial intelligence Computer graphics Control engineering Robotics Mechatronics |
| topic_facet | Computer Science Computer Imaging, Vision, Pattern Recognition and Graphics Processor Architectures Control, Robotics, Mechatronics Artificial Intelligence (incl. Robotics) Computer science Microprocessors Artificial intelligence Computer graphics Control engineering Robotics Mechatronics |
| url | https://doi.org/10.1007/978-1-4613-1539-1 |
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