Visual Saliency Computation A Machine Learning Perspective /
Visual Saliency Computation A Machine Learning Perspective / [electronic resource] :
edited by Jia Li, Wen Gao.
- 1st ed. 2014.
- XII, 240 p. 100 illus. online resource.
- Image Processing, Computer Vision, Pattern Recognition, and Graphics, 8408 3004-9954 ; .
- Image Processing, Computer Vision, Pattern Recognition, and Graphics, 8408 .
Benchmark and evaluation metrics -- Location-based visual saliency computation -- Object-based visual saliency computation -- Learning-based visual saliency computation -- Mining cluster-specific knowledge for saliency ranking -- Removing label ambiguity in training saliency model -- Saliency-based applications -- Conclusions and future work.
This book covers fundamental principles and computational approaches relevant to visual saliency computation. As an interdisciplinary problem, visual saliency computation is introduced in this book from an innovative perspective that combines both neurobiology and machine learning. The book is also well-structured to address a wide range of readers, from specialists in the field to general readers interested in computer science and cognitive psychology. With this book, a reader can start from the very basic question of "what is visual saliency?" and progressively explore the problems in detecting salient locations, extracting salient objects, learning prior knowledge, evaluating performance, and using saliency in real-world applications. It is highly expected that this book will spark a great interest of research in the related communities in years to come.
9783319056425
10.1007/978-3-319-05642-5 doi
Computer vision.
Artificial intelligence.
Data mining.
Computer Vision.
Artificial Intelligence.
Data Mining and Knowledge Discovery.
TA1634
006.37
Benchmark and evaluation metrics -- Location-based visual saliency computation -- Object-based visual saliency computation -- Learning-based visual saliency computation -- Mining cluster-specific knowledge for saliency ranking -- Removing label ambiguity in training saliency model -- Saliency-based applications -- Conclusions and future work.
This book covers fundamental principles and computational approaches relevant to visual saliency computation. As an interdisciplinary problem, visual saliency computation is introduced in this book from an innovative perspective that combines both neurobiology and machine learning. The book is also well-structured to address a wide range of readers, from specialists in the field to general readers interested in computer science and cognitive psychology. With this book, a reader can start from the very basic question of "what is visual saliency?" and progressively explore the problems in detecting salient locations, extracting salient objects, learning prior knowledge, evaluating performance, and using saliency in real-world applications. It is highly expected that this book will spark a great interest of research in the related communities in years to come.
9783319056425
10.1007/978-3-319-05642-5 doi
Computer vision.
Artificial intelligence.
Data mining.
Computer Vision.
Artificial Intelligence.
Data Mining and Knowledge Discovery.
TA1634
006.37