Applications of Kernel CCA

This lecture explores the applications of Kernel Canonical Correlation Analysis (KCCA) in person identification, gene clustering, and object pose estimation. It compares KCCA with other techniques, demonstrating its effectiveness in mapping data to a common space. The lecture also discusses the correlation between heterogeneous datasets and the extraction of gene clusters with similarities. Additionally, it presents the construction of appearance models for estimating object poses from raw images, showcasing the advantages of using KCCA over traditional methods.