Object detection with textural to spectral domain adaptation

Techniques for object detection include training a first classifier to detect an object based on textural features and a second classifier to detect the object based on textural features and spectral features. A classifier relationship between the two classifiers is learned and used with the first classifier to detect other objects. If desired, the performance of the object detector can be improved by comparing the results of detecting objects with the first classifier and the classifier relationship versus detecting objects with the first and second classifier together, and modifying the classifier relationship based upon the comparison.