Deep Learning in Object Detection and Recognition

Description

This book discusses recent advances in object detection and recognition using deep learning methods, which have achieved great success in the field of computer vision and image processing. It provides a systematic and methodical overview of the latest developments in deep learning theory and its applications to computer vision, illustrating them using key topics, including object detection, face analysis, 3D object recognition, and image retrieval. The book offers a rich blend of theory and practice. It is suitable for students, researchers and practitioners interested in deep learning, computer vision and beyond and can also be used as a reference book. The comprehensive comparison of various deep-learning applications helps readers with a basic understanding of machine learning and calculus grasp the theories and inspires applications in other computer vision tasks. Front Matter ....Pages i-xvi An Overview of Deep Learning (Zhaoqiang Xia)....Pages 1-18 Deep Learning in Object Detection (Yanwei Pang, Jiale Cao)....Pages 19-57 Deep Learning in Face Recognition Across Variations in Pose and Illumination (Xiaoyue Jiang, Yaping Hou, Dong Zhang, Xiaoyi Feng)....Pages 59-90 Face Anti-spoofing via Deep Local Binary Pattern (Lei Li, Xiaoyi Feng)....Pages 91-111 Kinship Verification Based on Deep Learning (Xiaoting Wu, Xiaoyi Feng, Lei Li, Elhocine Boutellaa, Abdenour Hadid)....Pages 113-132 Deep Learning Architectures for Face Recognition in Video Surveillance (Saman Bashbaghi, Eric Granger, Robert Sabourin, Mostafa Parchami)....Pages 133-154 Deep Learning for 3D Data Processing (Zhenbao Liu, Zhizhong Han, Shuhui Bu)....Pages 155-187 Deep Learning-Based Descriptors for Object Instance Search (Jie Lin, Olivier Morère, Antoine Veillard, Vijay Chandrasekhar)....Pages 189-224