In this paper, a novel structure is proposed for human activity modeling using time sequential spatio-temporal texture primitives. Gabor filters, which are proven to be robust 2D texture representation tools, are extended to 3D domain to capture spatio-temporal texture features. A well known filtering algorithm and an unsupervised clustering algorithm, the Genetic Chromodynamics, are combined t...

We study lattice rescoring with knowledge scores for automatic speech recognition. Frame-based log likelihood ratio is adopted as a score measure of the goodness-of-fit between a speech segment and the knowledge sources. We evaluate our approach in two different applications: phone recognition, and connected digit continuous recognition. By incorporating knowledge scores obtained from 15 attrib...

In this paper, we propose a novel implementation of a minimax decision rule for continuous density hidden Markovmodel-based robust speech recognition. By combining the idea of the minimax decision rule with a normal Viterbi search, we derive a recursive minimax search algorithm, where the minimax decision rule is repetitively applied to determine the partial paths during the search procedure. B...

The development of quantum mechanics has led to some radical changes in the theory of computation. A quantum theory of computing has come up and has been applied to give fascinating theoretical results for problems such as prime factorization (Shor, 1994) for which polynomial-time algorithms are not yet known on a classical computer. In this paper, we take a look at whether they can speed up th...

In this paper, we investigate the use of nonlinear distortion of the electrical post-detection signal in order to design simple, yet very effective, maximum likelihood sequence detection (MLSD) receivers for optical communications with direct photo-detection. This distortion enables the use of standard Euclidean branch metrics in the Viterbi algorithm which implements MLSD. Our results suggest ...

The story of the Viterbi algorithm (VA) is told from a personal perspective. Applications both within and beyond communications are discussed. In brief summary, the VA has proved to be an extremely important algorithm in a surprising variety of fields.

Hidden Markov models are traditionally decoded by the Viterbi algorithm which finds the highest probability state path in the model. In recent years, several limitations of the Viterbi decoding have been demonstrated, and new algorithms have been developed to address them (Kall et al., 2005; Brejova et al., 2007; Gross et al., 2007; Brown and Truszkowski, 2010). In this paper, we propose a new ...

Viterbi Decoders (VDs) are today widely used as forward error correction (FEC) devices in many digital communications and multimedia products, including mobile (cellular) phones, video and audio broadcasting receivers, and modems. VDs are implementations of the Viterbi Algorithm (VA) used for decoding convolutional or trellis codes. The continuing success of convolutional and trellis codes for ...

In this paper, we propose a novel implementation of a minimax decision rule for continuous density hidden Markov model based robust speech recognition. By combining the idea of the minimax decision rule with a normal Viterbi search, we derive a recursive minimax search algorithm, where the minimax decision rule is repetitively applied to determine the partial paths during the search procedure. ...

In this paper we present a new disparity estimation algorithm. The algorithm combines the low computational load of Viterbi algorithm approaches with field consistency in all directions found in Markov Random Field approaches. The key step in the algorithm is the application of the Viterbi algorithm orthogonal to the epipolar lines in stead of parallel to them. Two disparity fields are obtained...