EOG is a very effective eye movement recording method, which is not only noninvasive, but also can record any eye movements' information. In order to extract some features come form these information contained in ...
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EOG is a very effective eye movement recording method, which is not only noninvasive, but also can record any eye movements' information. In order to extract some features come form these information contained in EOG automatically, this paper presents a novel EOG feature parameters extraction algorithm. The proposed algorithm includes three main parts. The first is endpoint detection unit which detects the startpoint and endpoint of EOG signals. The second is a preprocessor which consists of band-pass filter, frame blocking procedure and windowing step. The third is feature parameters extracting part which extracts EOG feature by a linear predictive coding model and converts LPC parameters to LPC cepstral (LPCC) coefficients. Finally, the paper gives experimental results.
Shot type is useful information for semantic sports video analysis. Most existing approaches utilize predefined rules and domain knowledge to derive shot types in sports video. Although these methods have achieved pro...
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ISBN:
(纸本)9781605588407
Shot type is useful information for semantic sports video analysis. Most existing approaches utilize predefined rules and domain knowledge to derive shot types in sports video. Although these methods have achieved promising results in some specific games, it is hard to extend them from one sport to another. To address this problem, we propose a generic approach to classify shots in sports video. Our approach utilizes bag of visual words model to represent key frame for each shot based on Scale Invariant Feature Transform (SIFT) feature points;either Support Vector Machine (SVM) or Probabilistic Latent Semantic Analysis (PLSA) are then employed to classify key frame to determine shot type. As our approach relies little on domain knowledge, it can be more easily extended to different sports. We have evaluated our shot classification approach over five types of sports video and have achieved promising results. To show the usefulness and effectiveness of our shot classification, we apply the results of shot type to detect events in basketball video via a generative-discriminative model. In addition, we have observed that some common visual parts frequently appear across various shots in the same sport or even different but relevant sports. For instance, soccer and basketball are relevant sports in the sense of field-ball game. Motivated by this observation, we attempt to alleviate the problem of insufficient sports video data in some applications by sharing these visual parts across different but relevant kinds of sports. Copyright 2009 ACM.
Typical synthetic aperture radar (SAR) images are two-dimensional, providing range and azimuth information, but furnish few details with respect to elevation. First of all, one approach to extend SAR to three-dimensio...
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ISBN:
(纸本)9781424444793;9781424444809
Typical synthetic aperture radar (SAR) images are two-dimensional, providing range and azimuth information, but furnish few details with respect to elevation. First of all, one approach to extend SAR to three-dimensional imaging is considered. The simplest implementation of this would replace the single antenna element by a linear array oriented vertically. Secondly, the outlining data and image processing for a three-dimensional application is introduced in detail in the paper. Finally, simulation results show that the proposed algorithm is effective, while maintaining good image quality in terms of the reconstructed target response.
In this paper, we characterize the trees with the largest Laplacian and adjacency spectral radii among all trees with fixed number of vertices and fixed maximal degree, respectively.
In this paper, we characterize the trees with the largest Laplacian and adjacency spectral radii among all trees with fixed number of vertices and fixed maximal degree, respectively.
This paper proposes a threshold RSA signature scheme with traceable signers. In such scheme, there is a trusted center (TC), which generates all system parameters, the secret keys and the corresponding public keys of ...
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Manually annotated corpora are valuable but scarce resources, yet for many annotation tasks such as treebanking and sequence labeling there exist multiple corpora with different and incompatible annotation guidelines ...
ISBN:
(纸本)9781932432459
Manually annotated corpora are valuable but scarce resources, yet for many annotation tasks such as treebanking and sequence labeling there exist multiple corpora with different and incompatible annotation guidelines or standards. This seems to be a great waste of human efforts, and it would be nice to automatically adapt one annotation standard to another. We present a simple yet effective strategy that transfers knowledge from a differently annotated corpus to the corpus with desired annotation. We test the efficacy of this method in the context of Chinese word segmentation and part-of-speech tagging, where no segmentation and POS tagging standards are widely accepted due to the lack of morphology in Chinese. Experiments show that adaptation from the much larger People's Daily corpus to the smaller but more popular Penn Chinese Treebank results in significant improvements in both segmentation and tagging accuracies (with error reductions of 30.2% and 14%, respectively), which in turn helps improve Chinese parsing accuracy.
A hybrid lifting wavelet-like transform scheme is successfully applied to the solution of electric field integral equation using Rao-Wilton-Glisson basis functions. To speed up the matrix transform process, the liftin...
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A hybrid lifting wavelet-like transform scheme is successfully applied to the solution of electric field integral equation using Rao-Wilton-Glisson basis functions. To speed up the matrix transform process, the lifting scheme is adopted. Numerical examples of different three-dimensional perfectly electric conducting objects are considered. Compared with the method of moments, the proposed matrix transform scheme can save considerable CPU time and memory.
This paper presents a framework with two automatic tasks targeting large-scale and low quality sports video archives collected from online video streams. The framework is based on the bag of visual-words model using s...
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ISBN:
(纸本)9781605586083
This paper presents a framework with two automatic tasks targeting large-scale and low quality sports video archives collected from online video streams. The framework is based on the bag of visual-words model using speeded-up robust features (SURF). The first task is sports genre categorization based on hierarchical structure. Following on the second task which is based on automatically obtained genre, views are classified using support vector machines (SVMs). As a consequence, the views classification result can be used in video parsing and highlight extraction. As compared with state-of-the-art methods, our approach is fully automatic as well as domain knowledge free and thus provides a better extensibility. Furthermore, our dataset consists of 14 sport genres with 6850 minutes in total. Both sport genre categorization and view type classification have more than 80% accuracy rates, which validate this framework's robustness and potential in web-based applications. Copyright 2009 ACM.
Potential faults have greatly reduced the dependability of business processes, so fault diagnosis is becoming an important issue which aims at supporting self-healing service flow execution. The existing fault handlin...
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Potential faults have greatly reduced the dependability of business processes, so fault diagnosis is becoming an important issue which aims at supporting self-healing service flow execution. The existing fault handling mechanism provided by BPEL can only identify the faults which have been pre-defined in standards or by users. However, unexpected faults are also the main cause of failures in service flow execution. Therefore an effective diagnosis approach is needed to solve this problem. In this paper, we propose a logic-based approach for diagnosing unexpected faults in Web service flows. This approach uses dynamic description logic (DDL) to model business processes, and diagnoses faults based on DDL reasoning. We provide the DDL-based diagnosing algorithm, which takes process description and runtime information as inputs, and returns the related information of possible faults as the result. Moreover, to improve the efficiency of online diagnosis, the incremental DDL-based diagnosing algorithm is presented. Experimental results on a demo system show the effectiveness of this approach.
This paper presents a fast method for detecting multi-view cars in real-world scenes. Cars are artificial objects with various appearance changes, but they have relatively consistent characteristics in structure that ...
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This paper presents a fast method for detecting multi-view cars in real-world scenes. Cars are artificial objects with various appearance changes, but they have relatively consistent characteristics in structure that consist of some basic local elements. Inspired by this, we propose a novel set of image strip features to describe the appearances of those elements. The new features represent various types of lines and arcs with edge-like and ridge-like strip patterns, which significantly enrich the simple features such as haar-like features and edgelet features. They can also be calculated efficiently using the integral image. Moreover, we develop a new complexity-aware criterion for RealBoost algorithm to balance the discriminative capability and efficiency of the selected features. The experimental results on widely used single view and multi-view car datasets show that our approach is fast and has good performance.
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