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- W2348789690 abstract "The traditional feature-based video scenes' classification algorithm usually use fixed quantifying methods,which do not fully use all the information in the process of quantifying.This paper proposed an adaptive quantifying method,which performs non-uniform quantization for both the location and direction of the optical flow.This method can maximize the retention of the characteristic information obtained from the featured-based statistical distribution to improve the final performance of the algorithm.The theory of the adaptive quantifying algorithm is analyzed in detail,the steps are given.Then the results are compared with which just using traditional quantifying methods.The results show that the improved algorithm can reduce dictionary size of the LDA model and improve the operational efficiency.On the other hand,the improved algorithm has higher successful detection rate than the traditional algorithms,which effectively improves the performance of the algorithm." @default.
- W2348789690 created "2016-06-24" @default.
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- W2348789690 date "2012-01-01" @default.
- W2348789690 modified "2023-09-28" @default.
- W2348789690 title "Video Scene Classification Algorithm Based on Adaptive-quantifying LDA Model" @default.
- W2348789690 hasPublicationYear "2012" @default.
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