Wenyu Jiang

On improving the collision property of robust hashing based on projections

In this paper, we study the collision property of one of the robust hash functions proposed in [1]. This method was originally proposed for robust hash generation from blocks of image data and is based on projection of image block data on pseudo-random matrices. We show that collision performance of this robust hash function is not optimal when used to extract hash bits from a moment invariants feature matrix for video fingerprinting. We identify that the collision performance of this hash extraction method could be improved if the pseudo-random matrices are selected carefully. We propose two methods that use an offline training set to improve the collision property. Both of the methods attempt to select the matrices that minimize cross-correlation among the projected features. The first method uses an iterative procedure to select the matrices that satisfy a cross-correlation threshold. The second method used Singular Value Decomposition (SVD) of the feature covariance matrix and hence the crosscorrelation of the projected values is zero. We show the improved collision performance of both these methods on the same dataset. Also, we interpret the projection matrices obtained through the SVD procedure and show that they capture appearance and motion information from the moment invariants feature matrix.

Optimal configuration of hash table based multimedia fingerprint databases using weak bits

The increasingly large amount of digital multimedia content has created a need for technologies to search and identify multimedia files. Multimedia fingerprinting has been widely researched and successfully commercialized as a technology to trace and recognize both audio and video content. Most published research on multimedia fingerprinting focuses on the design of the fingerprinting extraction algorithm. The architecture of the fingerprinting database and the database query search algorithm has only been investigated in very few publications. In particular, no comprehensive mathematical models describing the accuracy of database query algorithms have been developed. Therefore, most performance evaluations of fingerprint system rely on experimental data. In this paper, we develop an analytic model to describe the operation of hash-table based multimedia fingerprinting databases. It allows to predict the accuracy of a fingerprinting query algorithm as a function of the statistical distribution of the fingerprints and the specific design of the fingerprint database.

Optimal choice of FEC parameters to protect against queueing losses in wireless networks

This paper proposes algorithms to determine an optimal choice of the FEC parameters (n, k) to mitigate against the effects of packet loss due to buffer overflow at a wireless base station on multimedia traffic. To solve this problem, we develop analytic models of the considered network scenarios that take into account traffic the arrival rates, the channel loss characteristics, and the size of the buffer at the wireless base station. We develop an iterative procedure to compute the packet loss probabilities after FEC recovery and verify the analytical results via simulation.

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.

Optimal Parameter Settings for Forward Error Correction Schemes for Multimedia Streaming over Wireless Networks

This paper investigates algorithms to determine an optimal choice of the FEC parameters (n, k) to mitigate the effects of packet loss due to buffer overflow at a wireless base station on multimedia traffic. We develop an analytic model of the considered network scenario that takes into account the traffic arrival rates, the channel loss characteristics, the size of the buffer at the wireless access point, and the influence of the FEC parameters on the packet loss. Applying the theory of recurrent linear equations, we present a new approach to establish a closed form solution of the underlying Markov model for the buffer occupancy and verify the analytical results via simulations