Jehanzeb Mirza, Leonid Karlinsky, et al.
NeurIPS 2023
On-line collections of images are growing larger and more common, and tools are needed to efficiently manage, organize, and navigate through them. The authors have developed a prototype system called QBIC which allows complex multi-object and multi-feature queries of large image databases. The queries are based on image content-the colors, textures, shapes, and positions of images and the objects/regions they contain. The system computes numeric features to represent the image properties and uses similarity measures based on these features for image retrieval. The focus of the paper is its user interface which allows a user to graphically pose and refine queries based on multiple visual properties of images and their objects.
Jehanzeb Mirza, Leonid Karlinsky, et al.
NeurIPS 2023
Hagen Soltau, Lidia Mangu, et al.
ASRU 2011
Diganta Misra, Muawiz Chaudhary, et al.
CVPRW 2024
Hans-Werner Fink, Heinz Schmid, et al.
Journal of the Optical Society of America A: Optics and Image Science, and Vision