Feature Extraction and Image Processing for Computer Vision 4/e
Nixon, Mark, Aguado, Alberto S.
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Feature Extraction and Image Processing for Computer Vision, Fourth Edition, describes basic principles, theories and techniques used to design visual search and recognition engines. The book explores how visual features are extracted and quantized, how an indexing system is built, includes comparisons to alternative schemes, and presents cutting-edge techniques, like deep learning. From the feature end, users will find out how hash functions transfer high-dimensional feature descriptors into compact binary code. From the model end, the book discusses recent advances in compressing and accelerating large, deep learning models (like convolutional neural networks) to fit into mobile and robotic memory storage.
- Introduces the building blocks of visual search and recognition engines
- Provides detailed reviews of visual feature hashing
- Contains reviews of deep learning model compression
- Presents the latest cutting-edge research, such as compact descriptors for visual search and visual feature hashing