Tomas Pajdla – författare

A unified view of the use of computer vision technology for different types of vehicles

Computer Vision in Vehicle Technology focuses on computer vision as on-board technology, bringing together fields of research where computer vision is progressively penetrating: the automotive sector, unmanned aerial and underwater vehicles. It also serves as a reference for researchers of current developments and challenges in areas of the application of computer vision, involving vehicles such as advanced driver assistance (pedestrian detection, lane departure warning, traffic sign recognition), autonomous driving and robot navigation (with visual simultaneous localization and mapping) or unmanned aerial vehicles (obstacle avoidance, landscape classification and mapping, fire risk assessment).

The overall role of computer vision for the navigation of different vehicles, as well as technology to address on-board applications, is analysed.

Key features:

This is essential reading for computer vision researchers, as well as engineers working in vehicle technologies, and students of computer vision.

A unified view of the use of computer vision technology for different types of vehicles

Computer Vision in Vehicle Technology focuses on computer vision as on-board technology, bringing together fields of research where computer vision is progressively penetrating: the automotive sector, unmanned aerial and underwater vehicles. It also serves as a reference for researchers of current developments and challenges in areas of the application of computer vision, involving vehicles such as advanced driver assistance (pedestrian detection, lane departure warning, traffic sign recognition), autonomous driving and robot navigation (with visual simultaneous localization and mapping) or unmanned aerial vehicles (obstacle avoidance, landscape classification and mapping, fire risk assessment).

The overall role of computer vision for the navigation of different vehicles, as well as technology to address on-board applications, is analysed.

Key features:

This is essential reading for computer vision researchers, as well as engineers working in vehicle technologies, and students of computer vision.

The total of 254 contributions was carefully reviewed and selected from 768 submissions during two rounds of reviewing and improvement. The papers focus on the following topics:

Part I: 3D computer vision; segmentation and grouping

Part II: low-level vision, image processing; motion and tracking

Part III: recognition and detection; optimization, statistical methods, and learning; robot vision

Part V: face, pose, action, and gesture; video analysis and event recognition; biomedical image analysis

Part VI: applications of computer vision; vision for X; datasets and performance analysis

*The conference was held virtually.

The total of 254 contributions was carefully reviewed and selected from 768 submissions during two rounds of reviewing and improvement. The papers focus on the following topics:

Part I: 3D computer vision; segmentation and grouping

Part II: low-level vision, image processing; motion and tracking

Part III: recognition and detection; optimization, statistical methods, and learning; robot vision

Part V: face, pose, action, and gesture; video analysis and event recognition; biomedical image analysis

Part VI: applications of computer vision; vision for X; datasets and performance analysis

*The conference was held virtually.

The total of 254 contributions was carefully reviewed and selected from 768 submissions during two rounds of reviewing and improvement. The papers focus on the following topics:

Part I: 3D computer vision; segmentation and grouping

Part II: low-level vision, image processing; motion and tracking

Part III: recognition and detection; optimization, statistical methods, and learning; robot vision

Part V: face, pose, action, and gesture; video analysis and event recognition; biomedical image analysis

Part VI: applications of computer vision; vision for X; datasets and performance analysis

*The conference was held virtually.

The total of 254 contributions was carefully reviewed and selected from 768 submissions during two rounds of reviewing and improvement. The papers focus on the following topics:

Part I: 3D computer vision; segmentation and grouping

Part II: low-level vision, image processing; motion and tracking

Part III: recognition and detection; optimization, statistical methods, and learning; robot vision

Part V: face, pose, action, and gesture; video analysis and event recognition; biomedical image analysis

Part VI: applications of computer vision; vision for X; datasets and performance analysis

*The conference was held virtually.

The total of 254 contributions was carefully reviewed and selected from 768 submissions during two rounds of reviewing and improvement. The papers focus on the following topics:

Part I: 3D computer vision; segmentation and grouping

Part II: low-level vision, image processing; motion and tracking

Part III: recognition and detection; optimization, statistical methods, and learning; robot vision

Part V: face, pose, action, and gesture; video analysis and event recognition; biomedical image analysis

Part VI: applications of computer vision; vision for X; datasets and performance analysis

*The conference was held virtually.

The total of 254 contributions was carefully reviewed and selected from 768 submissions during two rounds of reviewing and improvement. The papers focus on the following topics:

Part I: 3D computer vision; segmentation and grouping

Part II: low-level vision, image processing; motion and tracking

Part III: recognition and detection; optimization, statistical methods, and learning; robot vision

Part V: face, pose, action, and gesture; video analysis and event recognition; biomedical image analysis

Part VI: applications of computer vision; vision for X; datasets and performance analysis

*The conference was held virtually.

The seven-volume set comprising LNCS volumes 8689-8695 constitutes the refereed proceedings of the 13th European Conference on Computer Vision, ECCV 2014, held in Zurich, Switzerland, in September 2014.

The 363 revised papers presented were carefully reviewed and selected from 1444 submissions. The papers are organized in topical sections on tracking and activity recognition; recognition; learning and inference; structure from motion and feature matching; computational photography and low-level vision; vision; segmentation and saliency; context and 3D scenes; motion and 3D scene analysis; and poster sessions.