METHOD AND APPARATUS FOR IMAGE CLASSIFICATION WITH JOINT FEATURE ADAPTATION AND CLASSIFIER LEARNING

摘要

A technique for improving the performance of image classification systems is proposed which consists of learning an adaptation architecture on top of the input features jointly with linear classifiers, e.g., SVM. This adaptation method is agnostic to the type of input feature and applies either to features built using aggregators, e.g., BoW, FV, or to features obtained from the activations or outputs from DCNN layers. The adaptation architecture may be single (shallow) or multi-layered (deep). This technique achieves a higher performance compared to current state of the art classification systems.

主权项

1. A method of generating feature-adapted image classifiers for classifying images comprising:
accessing a plurality of training images; generating feature vectors for said training images; transforming said feature vectors with an input transform; generating said feature-adapted image classifiers and a feature adapted transform as a function of said transformed feature vectors and input image classifiers by jointly training said input image classifiers with said transformed feature vectors; and providing said feature-adapted image classifiers and said feature-adapted transform.