Design and implementation of real-time multi-sensor vision systems. ([2017])
- Record Type:
- Book
- Title:
- Design and implementation of real-time multi-sensor vision systems. ([2017])
- Main Title:
- Design and implementation of real-time multi-sensor vision systems
- Further Information:
- Note: Vladan Popovic, Kerem Seyid, Omer Cogal, Abdulkadir Akin, Yusuf Leblebici, authors.
- Authors:
- Popovic, Vladan
- Other Names:
- Seyid, Kerem
Cogal, Omer
Akin, Abdulkadir
Leblebici, Yusuf - Contents:
- Preface; Contents; 1 Introduction; 1.1 Computational Imaging; 1.2 Bridging the Performance Gap; 1.3 Miniaturized Panoramic Imaging; 1.4 Insect Eyes; 1.4.1 Bio-Mimicking Problem of Insect Eyes; 1.5 Key Contributions of the Book; 1.6 Book Outline; References; 2 State-of-the-Art Multi-Camera Systems; 2.1 Panorama Stitching Algorithms; 2.2 Camera Systems for Panorama Creation; 2.2.1 Single Camera Systems; 2.2.2 Catadioptric Systems; 2.2.3 Polydioptric Systems; 2.2.4 Commercial Cameras; 2.2.5 Light-Field and Unconventional Cameras; 2.3 Miniaturized Panoramic Camera Systems. 2.3.1 Insect Eye-Mimicking Systems Based on Micro-Machining Techniques2.3.2 Large FOV Imaging for Medical Endoscopy; 2.4 Depth Estimation Camera Systems and Approaches; 2.5 Conclusion; References; 3 Panorama Construction Algorithms; 3.1 Fundamentals of Image Formation; 3.2 Image Stitching; 3.2.1 Sphere Discretization; 3.2.2 Grid Refinement; 3.3 Vignetting Correction; 3.4 Alpha Blending; 3.5 Gaussian Blending; 3.5.1 Adaptive Gaussian Blending; 3.6 Multi-Band Blending; 3.6.1 Choice of Filters; 3.7 Panorama Generation as an Inference Problem; 3.7.1 Proposed Approach; 3.7.2 Graph Representation. 3.7.3 Accurate Prior Estimation from Spherical Model3.7.4 Experimental Results; 3.8 Inter-Camera Pixel Intensity Differences and Its Applications; 3.8.1 Object Boundary Detection; 3.8.2 Inter-Camera Pixel Intensity Differences as Inference Evidences; 3.9 Conclusion; References; 4 Omnidirectional Multi-Camera SystemsPreface; Contents; 1 Introduction; 1.1 Computational Imaging; 1.2 Bridging the Performance Gap; 1.3 Miniaturized Panoramic Imaging; 1.4 Insect Eyes; 1.4.1 Bio-Mimicking Problem of Insect Eyes; 1.5 Key Contributions of the Book; 1.6 Book Outline; References; 2 State-of-the-Art Multi-Camera Systems; 2.1 Panorama Stitching Algorithms; 2.2 Camera Systems for Panorama Creation; 2.2.1 Single Camera Systems; 2.2.2 Catadioptric Systems; 2.2.3 Polydioptric Systems; 2.2.4 Commercial Cameras; 2.2.5 Light-Field and Unconventional Cameras; 2.3 Miniaturized Panoramic Camera Systems. 2.3.1 Insect Eye-Mimicking Systems Based on Micro-Machining Techniques2.3.2 Large FOV Imaging for Medical Endoscopy; 2.4 Depth Estimation Camera Systems and Approaches; 2.5 Conclusion; References; 3 Panorama Construction Algorithms; 3.1 Fundamentals of Image Formation; 3.2 Image Stitching; 3.2.1 Sphere Discretization; 3.2.2 Grid Refinement; 3.3 Vignetting Correction; 3.4 Alpha Blending; 3.5 Gaussian Blending; 3.5.1 Adaptive Gaussian Blending; 3.6 Multi-Band Blending; 3.6.1 Choice of Filters; 3.7 Panorama Generation as an Inference Problem; 3.7.1 Proposed Approach; 3.7.2 Graph Representation. 3.7.3 Accurate Prior Estimation from Spherical Model3.7.4 Experimental Results; 3.8 Inter-Camera Pixel Intensity Differences and Its Applications; 3.8.1 Object Boundary Detection; 3.8.2 Inter-Camera Pixel Intensity Differences as Inference Evidences; 3.9 Conclusion; References; 4 Omnidirectional Multi-Camera Systems Design; 4.1 Introduction; 4.2 Image Acquisition Module; 4.3 System-Level Analysis; 4.3.1 System Memory and Bandwidth Constraints; 4.4 Top-Level Architecture; 4.5 Implementation of the Image Processing Unit; 4.5.1 Angle and Omega Vector Generation. 4.5.2 Camera Selection and Weight Calculation4.5.2.1 Dot Product and Square Root Sub-blocks; 4.5.3 Pixel Position Generation; 4.5.3.1 Sub-blocks of Pixel Position Generator; 4.5.4 Image Blending; 4.6 Experimental Results of the Panoptic System; 4.7 User Interface and Display; 4.8 Conclusion; References; 5 Miniaturization of Multi-Camera Systems; 5.1 Introduction; 5.2 Opto-Mechanical System Design; 5.2.1 Effect of Single Camera Dimensions; 5.2.2 Proposed Camera Placement for Miniaturized Camera Model; 5.2.3 Calibration; 5.2.4 Neural Superposition Virtual Ommatidia; 5.2.5 Illumination. 5.3 Circuit and Embedded System Design5.3.1 Single Camera Interface; 5.3.2 System Level Design Considerations; 5.3.3 Image Processing Hardware; 5.4 Results; 5.4.1 Visual Results; 5.4.2 Efficiency of the System Size; 5.4.3 Comparison with Different Insect Eye-Based Systems; 5.4.4 Hardware Implementation Results; 5.5 Discussion and Future Directions; 5.6 Conclusion; References; 6 Interconnected Network of Cameras; 6.1 Introduction; 6.2 Distributed and Parallel Implementation of Omnidirectional Vision Reconstruction; 6.2.1 Distributed and Parallel Algorithm; 6.2.2 Processing Demands. … (more)
- Publisher Details:
- Cham, Switzerland : Springer
- Publication Date:
- 2017
- Extent:
- 1 online resource
- Subjects:
- 621.367
620
Engineering
Image processing
Multisensor data fusion
Computer vision
TECHNOLOGY & ENGINEERING -- Mechanical
Computer vision
Image processing
Multisensor data fusion
Engineering
Circuits and Systems
Signal, Image and Speech Processing
Electronics and Microelectronics, Instrumentation
Technology & Engineering -- Electronics -- General
Imaging systems & technology
Electronics engineering
Systems engineering
Electronics
Technology & Engineering -- Electronics -- Circuits -- General
Circuits & components
Electronic books - Languages:
- English
- ISBNs:
- 9783319590578
- Related ISBNs:
- 331959057X
9783319590561
3319590561 - Notes:
- Note: Includes bibliographical references.
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- Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
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- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD.DS.365559
- Ingest File:
- 01_341.xml