Design and implementation of real-time multi-sensor vision systems

This book discusses the design of multi-camera systems and their application to fields such as the virtual reality, gaming, film industry, medicine, automotive industry, drones, etc. The authors cover the basics of image formation, algorithms for stitching a panoramic image from multiple cameras, an...

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Bibliographic Details
Main Author Popovic, Vladan (Author)
Other Authors Seyid, Kerem, Cogal, Omer, Akin, Abdulkadir, Leblebici, Yusuf
Format Electronic eBook
LanguageEnglish
Published Cham, Switzerland : Springer, [2017]
Subjects
Image processing.
Multisensor data fusion.
Computer vision.
elektronické knihy
electronic books
Online AccessFull text
ISBN9783319590578
9783319590561
Physical Description1 online resource

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Table of 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 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.

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