FaceTracer: A Search Engine for Large Collections of Images with Faces
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part IV
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Scenic photo quality assessment with bag of aesthetics-preserving features
MM '11 Proceedings of the 19th ACM international conference on Multimedia
Semi-supervised face image retrieval using sparse coding with identity constraint
MM '11 Proceedings of the 19th ACM international conference on Multimedia
The ACM Multimedia Grand Challenge 2011 in a nutshell
ACM SIGMultimedia Records
People search and activity mining in large-scale community-contributed photos
Proceedings of the 20th ACM international conference on Multimedia
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With the explosive growth of camera devices, people can freely take photos to capture moments of life, especially the ones accompanied with friends and family. Therefore, a better solution to organize the increasing number of personal or group photos is highly required. In this paper, we propose a novel way to search for face images according facial attributes and face similarity of the target persons. To better match the face layout in mind, our system allows the user to graphically specify the face positions and sizes on a query "canvas," where each attribute or identity is defined as an "icon" for easier representation. Moreover, we provide aesthetics filtering to enhance visual experience by removing candidates of poor photographic qualities. The scenario has been realized on a touch device with an intuitive user interface. With the proposed block-based indexing approach, we can achieve near real-time retrieval (0.1 second on average) in a large-scale dataset (more than 200k faces in Flickr images).