Computer Vision

This comprehensive textbook delves into image analysis techniques and real-world applications, emphasizing deep learning and engineering principles. It serves as both a course resource and a reference for computer vision research.

Computer Vision: Algorithms and Applications delves into the diverse techniques employed for image analysis and interpretation. It highlights practical, real-world applications of computer vision, ranging from specialized tasks like image search and autonomous navigation to more accessible consumer-level activities that students can apply to their own photos and videos. This comprehensive resource goes beyond merely providing “recipes” for problem-solving; it adopts a scientific approach to understanding computer vision challenges.

The textbook is structured to support active learning and project-based courses, offering guidance in the introduction for tailoring the material to various educational settings. It includes updated content on deep learning and applications such as mobile computational photography, autonomous navigation, and augmented reality. Each chapter concludes with exercises that emphasize algorithm testing and suggests small mid-term projects, fostering hands-on experience.

With 1,500 new citations and 200 new figures reflecting significant advancements over the past decade, this book is suitable for upper-level undergraduate and graduate courses in computer science or engineering. It emphasizes fundamental techniques that operate effectively in real-world scenarios while encouraging students to explore their creativity. Additionally, the appendices provide supplementary material on linear algebra, numerical methods, estimation theory, datasets, and software, making this text a valuable reference for both students and professionals in the field of computer vision.