This paper presents a video context enhancement method for night surveillance. The basic idea is to extract and fuse the meaningful information of video sequence captured from a fixed camera under different illuminati...This paper presents a video context enhancement method for night surveillance. The basic idea is to extract and fuse the meaningful information of video sequence captured from a fixed camera under different illuminations. A unique characteristic of the algorithm is to separate the image context into two classes and estimate them in different ways. One class contains basic surrounding scene in- formation and scene model, which is obtained via background modeling and object tracking in daytime video sequence. The other class is extracted from nighttime video, including frequently moving region, high illumination region and high gradient region. The scene model and pixel-wise difference method are used to segment the three regions. A shift-invariant discrete wavelet based image fusion technique is used to integral all those context information in the final result. Experiment results demonstrate that the proposed approach can provide much more details and meaningful information for nighttime video.展开更多
This letter addresses several key issues in the process of model-based optical metrology, including three dimensional (3D) sensing, calibration, registration and fusion of range images, geometric representation, and v...This letter addresses several key issues in the process of model-based optical metrology, including three dimensional (3D) sensing, calibration, registration and fusion of range images, geometric representation, and visualization of reconstructed 3D model by taking into account the shape measurement of 3D complex structures,and some experimental results are presented.展开更多
Laser cleaning is a highly nonlinear physical process for solving poor single-modal(e.g., acoustic or vision)detection performance and low inter-information utilization. In this study, a multi-modal feature fusion net...Laser cleaning is a highly nonlinear physical process for solving poor single-modal(e.g., acoustic or vision)detection performance and low inter-information utilization. In this study, a multi-modal feature fusion network model was constructed based on a laser paint removal experiment. The alignment of heterogeneous data under different modals was solved by combining the piecewise aggregate approximation and gramian angular field. Moreover, the attention mechanism was introduced to optimize the dual-path network and dense connection network, enabling the sampling characteristics to be extracted and integrated. Consequently, the multi-modal discriminant detection of laser paint removal was realized. According to the experimental results, the verification accuracy of the constructed model on the experimental dataset was 99.17%, which is 5.77% higher than the optimal single-modal detection results of the laser paint removal. The feature extraction network was optimized by the attention mechanism, and the model accuracy was increased by 3.3%. Results verify the improved classification performance of the constructed multi-modal feature fusion model in detecting laser paint removal, the effective integration of acoustic data and visual image data, and the accurate detection of laser paint removal.展开更多
Multimodality image registration and fusion are essential steps in building 3-D models from remotesensing data. We present in this paper a neural network technique for the registration and fusion of multimodali-ty rem...Multimodality image registration and fusion are essential steps in building 3-D models from remotesensing data. We present in this paper a neural network technique for the registration and fusion of multimodali-ty remote sensing data for the reconstruction of 3-D models of terrain regions. A FeedForward neural network isused to fuse the intensity data sets with the spatial data set after learning its geometry. Results on real data arepresented. Human performance evaluation is assessed on several perceptual tests in order to evaluate the fusionresults.展开更多
A smart Human Interface （HCI） replacing conventional mouse interface is proposed. The interface is able to control and command action with only hand. Four finger motions （left click, right dick, hold, drag） are u...A smart Human Interface （HCI） replacing conventional mouse interface is proposed. The interface is able to control and command action with only hand. Four finger motions （left click, right dick, hold, drag） are used to command the interface. Also the authors materialiae cursor movement control using image processing The measure what they use for inference is entropy of Electromyogram （EMG） signal, Gaussian modeling and likelihood estimation. In image processing for cursor control, they use color recognition to get the center point of finger tip from marker, and map the point onto cursor. Accuracy of finger movement inference is over 95% and cursor control works naturally without delay. They materlalize whole system to check its performance and utility.展开更多
A new method based on resolution degradation model is proposed to improve both spatial and spectral quality of the synthetic images. Some ETM+ panchromatic and multispectral images are used to assess the new method. I...A new method based on resolution degradation model is proposed to improve both spatial and spectral quality of the synthetic images. Some ETM+ panchromatic and multispectral images are used to assess the new method. Its spatial and spectral effects are evaluated by qualitative and quantitative measures and the results are compared with those of IHS, PCA, Brovey, OWT(Orthogonal Wavelet Transform) and RWT(Redundant Wavelet Transform). The results show that the new method can keep almost the same spatial resolution as the panchromatic images, and the spectral effect of the new method is as good as those of wavelet-based methods.展开更多
基金Supported by the National Natural Science Foundation of China (No.60634030 and No.60372085)
文摘This paper presents a video context enhancement method for night surveillance. The basic idea is to extract and fuse the meaningful information of video sequence captured from a fixed camera under different illuminations. A unique characteristic of the algorithm is to separate the image context into two classes and estimate them in different ways. One class contains basic surrounding scene in- formation and scene model, which is obtained via background modeling and object tracking in daytime video sequence. The other class is extracted from nighttime video, including frequently moving region, high illumination region and high gradient region. The scene model and pixel-wise difference method are used to segment the three regions. A shift-invariant discrete wavelet based image fusion technique is used to integral all those context information in the final result. Experiment results demonstrate that the proposed approach can provide much more details and meaningful information for nighttime video.
基金This work is supported by National Natural Science Foundationof China.(Grant No. 60275012)Natural Science Research Foundof Higher Education in Guangdong Province (Grant No. 04Z010)+1 种基金the Natural Science Foundation of Guangdong Province (GranNo. 06028584) the Research Project of Science & Technol-ogy from Shenzhen Government (Grant No.200619).
文摘This letter addresses several key issues in the process of model-based optical metrology, including three dimensional (3D) sensing, calibration, registration and fusion of range images, geometric representation, and visualization of reconstructed 3D model by taking into account the shape measurement of 3D complex structures,and some experimental results are presented.
基金Project(51875491) supported by the National Natural Science Foundation of ChinaProject(2021T3069) supported by the Fujian Science and Technology Plan STS Project,China。
文摘Laser cleaning is a highly nonlinear physical process for solving poor single-modal(e.g., acoustic or vision)detection performance and low inter-information utilization. In this study, a multi-modal feature fusion network model was constructed based on a laser paint removal experiment. The alignment of heterogeneous data under different modals was solved by combining the piecewise aggregate approximation and gramian angular field. Moreover, the attention mechanism was introduced to optimize the dual-path network and dense connection network, enabling the sampling characteristics to be extracted and integrated. Consequently, the multi-modal discriminant detection of laser paint removal was realized. According to the experimental results, the verification accuracy of the constructed model on the experimental dataset was 99.17%, which is 5.77% higher than the optimal single-modal detection results of the laser paint removal. The feature extraction network was optimized by the attention mechanism, and the model accuracy was increased by 3.3%. Results verify the improved classification performance of the constructed multi-modal feature fusion model in detecting laser paint removal, the effective integration of acoustic data and visual image data, and the accurate detection of laser paint removal.
文摘Multimodality image registration and fusion are essential steps in building 3-D models from remotesensing data. We present in this paper a neural network technique for the registration and fusion of multimodali-ty remote sensing data for the reconstruction of 3-D models of terrain regions. A FeedForward neural network isused to fuse the intensity data sets with the spatial data set after learning its geometry. Results on real data arepresented. Human performance evaluation is assessed on several perceptual tests in order to evaluate the fusionresults.
基金supported by the MKE(The Ministry of Knowledge Economy),Koreathe ITRC(Information Technology Research Center)support program supervised by the NIPA(National IT Industry Promotion Agency)(NIPA-2010-C1090-1021-0010)
文摘A smart Human Interface （HCI） replacing conventional mouse interface is proposed. The interface is able to control and command action with only hand. Four finger motions （left click, right dick, hold, drag） are used to command the interface. Also the authors materialiae cursor movement control using image processing The measure what they use for inference is entropy of Electromyogram （EMG） signal, Gaussian modeling and likelihood estimation. In image processing for cursor control, they use color recognition to get the center point of finger tip from marker, and map the point onto cursor. Accuracy of finger movement inference is over 95% and cursor control works naturally without delay. They materlalize whole system to check its performance and utility.
文摘A new method based on resolution degradation model is proposed to improve both spatial and spectral quality of the synthetic images. Some ETM+ panchromatic and multispectral images are used to assess the new method. Its spatial and spectral effects are evaluated by qualitative and quantitative measures and the results are compared with those of IHS, PCA, Brovey, OWT(Orthogonal Wavelet Transform) and RWT(Redundant Wavelet Transform). The results show that the new method can keep almost the same spatial resolution as the panchromatic images, and the spectral effect of the new method is as good as those of wavelet-based methods.
