Systematic design of indexing strategies for object recognition

The authors analyze how parameters of indexing based recognition systems affects their performance. The main result is that increasing the dimensionality of the indices leads to significantly improved discrimination, false positive suppression and reduced recognition times. With increase in index dimensionality, coarser quantization is required to allow index match in the presence of noise. The authors´ analysis also allows estimation of votes thresholds for recognition and estimation of the amount of occlusion that can be tolerated by indexing schemes for given levels of recognition confidence