Keyword Spotting in Poorly Printed Documents using Pseudo 2-D Hidden Markov Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Person Tracking in Real-World Scenarios Using Statistical Methods
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
VS '99 Proceedings of the Second IEEE Workshop on Visual Surveillance
A hidden markov model-based approach for face detection and recognition
A hidden markov model-based approach for face detection and recognition
Investigating Hidden Markov Models' Capabilities in 2D Shape Classification
IEEE Transactions on Pattern Analysis and Machine Intelligence
HMM-Based Action Recognition Using Contour Histograms
IbPRIA '07 Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part I
High speed biological sequence analysis with hiddenMarkov models on reconfigurable platforms
IEEE Transactions on Information Technology in Biomedicine - Special section on computational intelligence in medical systems
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This paper explores methods for hardware acceleration of Hidden Markov Model (HMM) decoding for the detection of persons in still images. Our architecture exploits the inherent structure of the HMM trellis to optimise a Viterbi decoder for extracting the state sequence from observation features. Further performance enhancement is obtained by computing the HMM trellis states in parallel. The resulting hardware decoder architecture is mapped onto a field programmable gate array (FPGA). The performance and resource usage of our design is investigated for different levels of parallelism. Performance advantages over software are evaluated. We show how this work contributes to a real-time system for person-tracking in video-sequences.