Design and implementation of real-time multi-sensor vision systems
Popovic, Vladan,
Design and implementation of real-time multi-sensor vision systems Vladan Popovic, Kerem Seyid, Omer Cogal, Abdulkadir Akin, Yusuf Leblebici, authors. - 1 recurso en línea
SpringerLink
Incluye referencias bibliográficas
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
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, and multiple real-time hardware system architectures, in order to have panoramic videos. Several specific applications of multi-camera systems are presented, such as depth estimation, high dynamic range imaging, and medical imaging.
331959057X 9783319590578
Visión por ordenador
TA1637 / 2017 EB
Design and implementation of real-time multi-sensor vision systems Vladan Popovic, Kerem Seyid, Omer Cogal, Abdulkadir Akin, Yusuf Leblebici, authors. - 1 recurso en línea
SpringerLink
Incluye referencias bibliográficas
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
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, and multiple real-time hardware system architectures, in order to have panoramic videos. Several specific applications of multi-camera systems are presented, such as depth estimation, high dynamic range imaging, and medical imaging.
331959057X 9783319590578
Visión por ordenador
TA1637 / 2017 EB