Description
Book Synopsis1 Why modeling attention in computers?, M. Mancas, V. Ferrera, N. Riche.- 2 What is attention?, M. Mancas.- 3 How to measure attention?, M. Mancas, V. Ferrera.- 4 Where: Human attention networks and their dysfunctions after brain damage, T. Seidel Malkinson, P. Bartolomeo.- 5 Attention and Signal Detection: A Practical Guide, V. Ferrera.- 6 Effects of Attention in Visual Cortex: Linking Single Neuron Physiology to Visual Detection and Discrimination, V. Ferrera.- 7 Modeling attention in engineering, M. Mancas.- 8 Bottom-Up Visual Attention for Still Images: a Global View, F. Stentiford.- 9 Bottom-up saliency models for still images: a practical review, N. Riche and M. Mancas.- 10 Bottom-up saliency models for videos: a practical review, N. Riche and M. Mancas.- 11 Databases for saliency models evaluation, N. Riche.- 12 Metrics for saliency models validation, N. Riche.- 13 Study of parameters affecting visual saliency assessment, N. Riche.- 14 Saliency models evaluation, N. Riche.- 15 Object-based Attention: cognitive and computational perspectives, A. Belardinelli.- 16 Multimodal saliency models for videos, Antoine Coutrot, Nathalie Guyader.- 17 Towards 3D visual saliency modelling, J. Leroy, N. Riche.- 18 Applications of saliency models, M. Mancas, O. Le Meur.- 19 Attentive Content-Based Image Retrieval, D. Awad, V. Courboulay, A. Revel.- 20 Saliency and Attention for Video Quality Assessment, D. Culibrk.- 21 Attentive Robots, S. Frintrop.- 22 Attention modeling: what are the next steps?, M. Mancas, V. Ferrera, N. Riche.- Index.
