Research in pattern recognition has exponentially increased in the past decades due to the improvement in both quality and resolution of imaging sensors and the dramatic increase in computational power. This increase has also been accompanied by smoothing the boundaries between different applications of pattern recognition, making it really interdisciplinary. The objective of this special issue is to invite original research contributions that address the broad challenges faced in pattern recognition. We look for recent advances in mathematical methods of pattern recognition as well as new applications in many scientific fields, ranging from science and engineering to economics and social activities.

We solicit articles in all fields of pattern recognition for solving various engineering problems including mathematical methods of object detection, localization and tracking, adaptive methods of pattern recognition, template and descriptor-based matching, video analysis and understanding, motion estimation, action recognition, deep learning techniques, and fast algorithms of pattern recognition. We believe the special issue will offer a timely collection of research updates to benefit the researchers and practitioners working in the broad computer vision and pattern recognition communities.

Potential topics include but are not limited to the following:

• Mathematical models and theory of pattern recognition
• Statistical, syntactic, and structural pattern recognition
• Advances in 2D/3D object detection and recognition
• Template and descriptor-based matching algorithms
• Automatic detection, recognition, and identification of target
• Occlusion and shadow detection
• Motion, tracking, and video analysis
• Deformable object tracking
• Deep learning techniques
• Highlight detection, action recognition, and event detection
• Document processing and recognition
• Applications and clinical studies