Deep Learning in Object Detection and Recognition

Discusses recent developments in deep learning and its applications in object detection and recognition

Covers key tasks of computer vision, including object detection, face detection, face recognition, 3D object recognition and image retrieval

Includes contributions written by leading experts in the respective fields

Provides several illustrations and experimental results explaining the different methods

Autorentext

**Xiaoyue Jiang received her Ph.D. degree in Computer Science and Technology from Northwestern Polytechnical University in 2006. From Xiaoyue Jiang received her Ph.D. degree in Computer Science and Technology from Northwestern Polytechnical University in 2006. From 2006 to 2012, she has worked in Vrije University of Brussels (Belgium), University of Birmingham (UK) and Queen's University of Belfast (UK) as assistant and associated research fellow, respectively. She has worked as associated professor at Northwestern Polytechnical University since 2012. Her research interests includes computer vision, image processing and pattern recognition. She has published more than 50 research papers and is currently senior fellow and secretary of Shaanxi Society of Image and Graphics. Abdenour Hadid** is an adjunct professor at the Center for Machine Vision and Signal Analysis at University of Oulu. He is the chairman of the Pattern Recognition Society of Finland. His research interests include biometrics and facial image analysis, local descriptors, machine learning and human-machine interaction. He has authored over 140

Inhalt

1. An Overview of Deep Learning.- 2. Object Detection In Deep Learning.- 3. Deep Learning in Face Recognition across Pose and Illumination.- 4. Face Anti-spoofing via Deep Local Binary Pattern.- 5. Face Anti-spoofing via Deep Local Binary Pattern.- 6. Deep Learning Architectures for Face Recognition in Video Surveillance.- 7. Deep learning for 3D data.- 8. Deep Learning based Descriptors for Object Instance Search.