Topic Title: Face and Person Recognition across Large Pose


Technical Area:

Computer Vision

Pattern Recognition




Identity recognition is a key component in many intelligent applications, such as video surveillance, business analytics, financial security, access control and so on. Especially for business analytics in physical store, we could track the consumers’ preferences based on their identity. Identity and big data could be combined further to enhance consumers’ shopping experiences. Currently, identity could be obtained through mobile APPs, Bluetooth, Wi-Fi or video camera. Among them, face (or person) recognition based on video camera is the most user-friend and device-free technology.


For user-friend experiences and easy deployment, we want to develop high performance face/person recognition algorithm, especially in crowded store or supermarket. To avoid person occlusion in crowded environment, video cameras are usually install at height > 3m in very large pitch angle (> 30 degree). In practice, we find that the large angle installment significantly degrades the recognition rate. Although many pose robust face recognition algorithms were proposed in the existing works, they mainly focus on the yaw angle. Dealing with both pitch and yaw angles together is still a challenge.


As compared with face recognition, person recognition (or re-identification, re-id) is naturally more robust to the pose variations. This is because person recognition is mainly based on holistic features, e.g., color and texture of clothes. Therefore, combing both face and person features to do recognition could be a reasonable research direction in order to improve the recognition rate across large pose.


We are looking for the researchers who are experts either in this field or the related fields and also keen to aim for the challenges and opportunities on this topic.



Aiming to “New Retail” scenarios, advanced large pose face and person recognition tries to solve the following practical problems:


Related Research Topics

Many sub-problems related to this topic have been studied for many years in academy and industry, which are listed as follows: