A framework of real time face tracking and recognition is presented, which integrates skin color based tracking and PCA/BPNN (principle component analysis/back propagation neural network) hybrid recognition techni...A framework of real time face tracking and recognition is presented, which integrates skin color based tracking and PCA/BPNN (principle component analysis/back propagation neural network) hybrid recognition techniques. The algorithm is able to track the human face against a complex background and also works well when temporary occlusion occurs. We also obtain a very high recognition rate by averaging a number of samples over a long image sequence. The proposed approach has been successfully tested by many experiments, and can operate at 20 frames/s on an 800 MHz PC.展开更多
Based on principal component analysis, the rules of clayey soil's behaviors affected by varied indices were studied. It was discovered that the common method of the single liquidity index IL used to determine the ...Based on principal component analysis, the rules of clayey soil's behaviors affected by varied indices were studied. It was discovered that the common method of the single liquidity index IL used to determine the consistency of silt-clay or silt-loam was not rational. It was more rational that the liquidity index IL combined with the void ratio e characterized the behavior of silt-clay. Similarly the index of e depicted the nature of sandy loam more rationally than IL. The method of predicting the pile shafted resistance by the two indices of e and IL, which was more accurate, was obtained by the methodology of back propagation (BP) artificial neural networks combined with principal component analysis. It was also observed that the pile shaft resistance increased with the increase of depth within a critical affect-depth ranging from 20 to 30 m, and the harder the clayey soil consistency was, the shallower the critical depth was.展开更多
文摘A framework of real time face tracking and recognition is presented, which integrates skin color based tracking and PCA/BPNN (principle component analysis/back propagation neural network) hybrid recognition techniques. The algorithm is able to track the human face against a complex background and also works well when temporary occlusion occurs. We also obtain a very high recognition rate by averaging a number of samples over a long image sequence. The proposed approach has been successfully tested by many experiments, and can operate at 20 frames/s on an 800 MHz PC.
文摘Based on principal component analysis, the rules of clayey soil's behaviors affected by varied indices were studied. It was discovered that the common method of the single liquidity index IL used to determine the consistency of silt-clay or silt-loam was not rational. It was more rational that the liquidity index IL combined with the void ratio e characterized the behavior of silt-clay. Similarly the index of e depicted the nature of sandy loam more rationally than IL. The method of predicting the pile shafted resistance by the two indices of e and IL, which was more accurate, was obtained by the methodology of back propagation (BP) artificial neural networks combined with principal component analysis. It was also observed that the pile shaft resistance increased with the increase of depth within a critical affect-depth ranging from 20 to 30 m, and the harder the clayey soil consistency was, the shallower the critical depth was.
