On deriving longer fingerprints from features based on projections

We propose three methods to derive longer fingerprints from features using projection based hashing methods. For this class of hashing methods, a feature matrix is projected onto a set of projection matrices. Then, the projected values are compared to a threshold to derive the hash bits. The methods proposed in this paper reduce the increase in average number of collisions per hour of content in the database by creating longer fingerprint codewords. The first method derives 56 fingerprint bits by projecting the feature matrix onto 56 projection matrices by deriving one bit from each projected value. The second method uses 36 projection matrices but derives 56 fingerprint bits by deriving varying number of bits from each projected value. The third method also 36 projection matrices but derives 56 bits by creating more features that capture the relationships between the projected values. We present experimental results comparing these three methods to a baseline method in terms of collision performance and robustness.