This paper proposes a method for robustly matching active appearance models (AAMs) on images with gross disturbances (outliers). The method consists of two steps. First, an initial residual is calculated by comparing ...
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ISBN:
(数字)9783540264316
ISBN:
(纸本)3540250522
This paper proposes a method for robustly matching active appearance models (AAMs) on images with gross disturbances (outliers). The method consists of two steps. First, an initial residual is calculated by comparing model and image appearance, and modes of the residual are analyzed. Second, all possible mode combinations are tested by evaluating an objective function. The objective function allows the selection of an outlier-free mode combination. Experiments demonstrate the ability of the robust matching method to successfully cope with outliers - compared to standard AAM matching, no degeneration of the model during matching occurs.
This paper presents a novel real-time signal processing system using for target tracking, it uses both ADSP21060 and FPGA to attain high performance and high-speed imageprocessing. It analyses the flexible hardware a...
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ISBN:
(纸本)0780390156
This paper presents a novel real-time signal processing system using for target tracking, it uses both ADSP21060 and FPGA to attain high performance and high-speed imageprocessing. It analyses the flexible hardware architecture based on the idea of reconfigurability and modularization, and discusses three main modules and extensibility of the hardware system. Then the implementation of the image pre-processing and target intelligent tracking algorithm is discussed in detail. The experimental result shows that the system processing rate reaches 30 frames per second. The system can automatically detect targets and output the tracking information in real-time.
Noise is a common phenomenon in many real-world optimizations. It has long been argued that evolutionary algorithm (EA) should be relatively robust against it. As a novel computing model in evolutionary computations, ...
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Noise is a common phenomenon in many real-world optimizations. It has long been argued that evolutionary algorithm (EA) should be relatively robust against it. As a novel computing model in evolutionary computations, estimation of distribution algorithm (EDA) is also encountered with it. This paper initially presents three dynamic models of EDA under the additively noisy environment with three different selection methods (proportional selection method, truncation selection method and tournament selection method). We verify that when the population size is infinite, EDA can converge to the global optimal point. This concept establishes the theoretic foundation for optimization of noisy fitness functions with EDA
Walsh-Haar function system that was first intruoduced by us is a new kind of function systems, and has a good global/local property. This function system is called Walsh ordering function system since its generation k...
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Walsh-Haar function system that was first intruoduced by us is a new kind of function systems, and has a good global/local property. This function system is called Walsh ordering function system since its generation kernel functions belong to Walsh ordering Walsh function system. We worked out a recursive property of the matrix WHKRm+1 corresponding to the first KR m+1 Walsh-Haar functions in Walsh-Haar function system, and we also proved that Walsh-Haar function system is perfect and orthogonal similar to Walsh function system and Haar function system. Thus, discrete Walsh-Haar transformation (DW-HT) is an orthogonal transformation that can be widely used in signal processing. In this paper, using the recursive property of the matrix WHKRm+1 and the fast algorithm of discrete Walsh transformation (DWT) in Walsh ordering, we have designed a fast algorithm of Walsh ordering DW-HT based on the bisection technique. The idea and method used in this paper can be used for designing fast algorithms of other ordering DW-HTs and other discrete orthogonal transformations.
This paper gives a robust motion detection and tracking solution for a video surveillance application on an airport's apron. As an outdoor application, the system must be capable of adapting to a wide range of wea...
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This paper gives a robust motion detection and tracking solution for a video surveillance application on an airport's apron. As an outdoor application, the system must be capable of adapting to a wide range of weather conditions and illumination changes, furthermore, the achromaticity of the scene and the presence of occlusions in the tracking process are issues considered in the selection of the motion detector and tracking system respectively. We propose an adapted mixture of Gaussiani model with RGB colour normalisation to detect mobile objects in the scene and a region tracking method based on significant mobile object features to track individuals and vehicles on the selected airport's apron. The performance of the proposed motion detector is evaluated using pixel-based performance metrics and compared with other existing methods. The capability of the application to handle partial occlusions is tested on the region tracker.
Many vision-related processing tasks, including edge detection and image segmentation, can be performed more easily when all objects in the scene are in good focus. However, in practice, this may not be always feasibl...
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Many vision-related processing tasks, including edge detection and image segmentation, can be performed more easily when all objects in the scene are in good focus. However, in practice, this may not be always feasible as optical lenses, especially those with long focal lengths, only have a limited depth of field. One classical approach to recover an everywhere-in-focus image is to use Laplacian pyramid image fusion. First, several source images with different focuses of the same scene are taken and decomposed into the low/high-frequency components image sequences. Within these decompositions, the high-frequency components image sequences with the largest magnitude are selected at each pixel location. Finally, the fused image can be recovered from the decomposed components image sequences. In the support vector machine (SVM), the pixels with larger support values have a physical meaning in the sense that they reveal relative more importance of the data points for contributing to the SVM model. In this paper, we use Laplacian pyramid for the multi resolution decomposition, and then replace the traditional salient features by support values of the mapped least squares (LS)-SVM for fusing image. Experimental results illustrate that the proposed method outperforms the traditional approach.
Target detection techniques play an important role in automatic target recognition (ATR) systems because overall ATR performance depends closely on detection results. In this paper, a novel method for fusion detection...
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Target detection techniques play an important role in automatic target recognition (ATR) systems because overall ATR performance depends closely on detection results. In this paper, a novel method for fusion detection of infrared weak targets based on multifeature distance map (MFDM) in image sequences is proposed. As for small weak targets, there are many features, such as local entropy, average gradient strength. These features depict the characteristics of small infrared targets and can be extracted. Multifeature-based fusion techniques are applied to detect such weak targets. The problem of detecting small targets is converted to search peak values in specified feature space where multifeature vectors space (MFVS) is considered. Distance map (DM) can be derived according to feature vectors and target detection is performed in DM. In order to accumulate energy of targets deeply and suppress background and clutters to a great extent, five distance maps obtained by corresponding five consecutive frames are utilized to fuse with average weight, which results in the fact that the contrast between targets and background including clutters are enlarged and that the feature peaks of targets are obvious different from background and clutters. After these steps, a contrast segmentation method is used to extract targets from complicated background on the fused DM. Actual infrared image sequences in background of sea and sky are applied to validate the proposed approach. Experimental results demonstrate the robustness of the proposed method with high performance.
This paper introduces the new qualitative and quantitative methods, which can diagnose breast tumors. Qualitative methods include blood vessel display inside and outside of pathological changes part of breast, display...
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Target detection and location in infrared clutter background is very important to infrared search and track system. Especially for small target detection in infrared image in background of sea and sky, there are no ge...
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Target detection and location in infrared clutter background is very important to infrared search and track system. Especially for small target detection in infrared image in background of sea and sky, there are no geometric and structure character to use. When targets such as ship and naval vessel sailing at long distance, they always appear around the sea-level line, and it is mixed with cloud and sea-wave clutter. It is difficult to segment and locate precisely. Background suppression based-on wavelet transformation is proposed in the paper. Wavelet decomposition makes it possible to analyze a signal both in time and frequency domains. In the paper infrared sea and key background images are processed. For their SNR is low and background is complex, using wavelet transformation decomposes an original image and extract approximate feature to reconstruct an image, which mainly includes background information. A new image would be obtained using background image subtracted from original image. There are mainly target and noise points left in the new image. By setting proper threshold, the target can be detected perfectly. At last, experiment results are given and show the method is practical.
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