Human-centric multimedia analysis is one of the fundamental problems in multimedia understanding. It is a very challenging problem that involves multiple tasks such as face detection and recognition, human pose estimation, human action detection, human-object interaction, person tracking, person re-identification, and so on. Today, ubiquitous multimedia sensors and large-scale computing infrastructures are producing at a rapid velocity a wide variety of big multi-modality data for human-centric analysis, which provides rich knowledge to tackle these challenges. Researchers have strived to push the limits of human-centric multimedia analysis in various applications, such as intelligent surveillance, retailing, fashion design, and services. Therefore, the purpose of this workshop is to: 1) bring together the state-of-the-art research on human-centric multimedia analysis; 2) call for a coordinated effort to understand the opportunities and challenges emerging in human-centric multimedia analysis; 3) identify key tasks and evaluate the state-of-the-art methods; 4) showcase innovative methodologies and ideas; 5) introduce interesting real-world human-centric multimedia analysis systems or applications; and 6) propose new real-world datasets and discuss future directions. We solicit original contributions in all fields of human-centric multimedia analysis that explore the multi-modality data to understand the behavior of humans. We believe this workshop will offer a timely collection of research updates to benefit researchers and practitioners in the broad multimedia communities. To this end, we solicit original research and survey papers in (but not limited to) the following topics:

• Face detection, recognition, face anti-spoofing, face landmark detection and parsing.
• Human detection, pose estimation, human parsing, and pose tracking.
• Human 3D shape estimation and reconstruction.
• Human gait recognition, person re-identification and person tracking.
• Human action recognition and detection
• Human activity recognition using non-visual sensors
• Human-computer interaction / Human object interaction
• Multimedia event detection
• Anomaly event detection
• Human crowd analysis