Codebook-free exemplar models for object detection

Traditional bag-of-features approaches often vector-quantise the features into a visual codebook. This process inevitably causes loss of information. Recently codebook-free methods that avoid the vector-quantisation step have become more popular. Used in conjunction with nearest-neighbour approaches these methods have shown remarkable classification performance. In this paper we show how to exploit the concept of nearest neighbour based classification for object detection. Our codebook-free exemplar model combines the classification power of nearest neighbour methods with a detection concept based on exemplar models. We demonstrate the performance of our proposed system on a real-world dataset of images of motorbikes.