Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Content-Based Image Retrieval at the End of the Early Years
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning-based linguistic indexing of pictures with 2--d MHMMs
Proceedings of the tenth ACM international conference on Multimedia
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
The Journal of Machine Learning Research
The Journal of Machine Learning Research
On image auto-annotation with latent space models
MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
PLSA-based image auto-annotation: constraining the latent space
Proceedings of the 12th annual ACM international conference on Multimedia
Evaluating the impact of selection noise in community-based web search
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Using One-Class and Two-Class SVMs for Multiclass Image Annotation
IEEE Transactions on Knowledge and Data Engineering
Hi-index | 0.00 |
This paper introduces a hierarchical process for propagating image annotations throughout a partially labelled database. Long-term learning, where users' query and browsing patterns are retained over multiple sessions, is used to guide the propagation of keywords onto image regions based on low-level feature distances. We demonstrate how singular value decomposition (SVD), normally used with latent semantic analysis (LSA), can be used to reconstruct a noisy image-session matrix and associate images with query concepts. These associations facilitate hierarchical filtering where image regions are matched based on shared parent concepts. A simple distance-based ranking algorithm is then used to determine keywords associated with regions.