Sunsern Cheamanunkul

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We have built a system that engages naive users in an audio-visual interaction with a computer in an unconstrained public space. We combine audio source localization techniques with face detection algorithms to detect and track the user throughout a large lobby. The sensors we use are an ad-hoc microphone array and a PTZ camera. To engage the user, the PTZ(More)
This paper presents a hardware architecture for increased performance of color classification. In our architecture, color classification, based on an AdaBoost algorithm, identifies a pixel as having the color of interest or not. We designed the proposed architecture using Verilog HDL and implemented the design in a Xilinx Virtex-5 FPGA. The architecture for(More)
The sensitivity of Adaboost to random label noise is a well-studied problem. LogitBoost, BrownBoost and RobustBoost are boosting algorithms claimed to be less sensitive to noise than AdaBoost. We present the results of experiments evaluating these algorithms on both synthetic and real datasets. We compare the performance on each of datasets when the labels(More)
The traditional k-NN classification rule predicts a label based on the most common label of the k nearest neighbors (the plurality rule). It is known that the plurality rule is optimal when the number of examples tends to infinity. In this paper we show that the plurality rule is sub-optimal when the number of labels is large and the number of examples is(More)
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