This paper investigates whether visual place recognition techniques can be used to provide pose estimation information for a visual SLAM system operating long-term in an environment where the appearance may change a great deal. It demonstrates that a combination of a conventional SURF feature detector and a condition-invariant feature descriptor such as HOG or conv3 can provide a method of determining the relative transformation between two images, even when there is both appearance change and rotation or viewpoint change.