This paper proposes a method to recognize human-object interactions by modeling context between human actions and interacted objects.Human-object interaction recognition is a challenging task due to severe occlusion b...This paper proposes a method to recognize human-object interactions by modeling context between human actions and interacted objects.Human-object interaction recognition is a challenging task due to severe occlusion between human and objects during the interacting process.Since that human actions and interacted objects provide strong context information,i.e.some actions are usually related to some specific objects,the accuracy of recognition is significantly improved for both of them.Through the proposed method,both global and local temporal features from skeleton sequences are extracted to model human actions.In the meantime,kernel features are utilized to describe interacted objects.Finally,all possible solutions from actions and objects are optimized by modeling the context between them.The results of experiments demonstrate the effectiveness of our method.展开更多
Process integration is the important aspect of product development process. The recent researches focus on project management, workflow management and process modeling. Based on the analysis of the process, product de...Process integration is the important aspect of product development process. The recent researches focus on project management, workflow management and process modeling. Based on the analysis of the process, product development process is divided into three levels according to different grains from macroscopy to microcosm. Our research concentrate on the workflow and the free-grained design process. According to the need of representing the data and the relationships among them for process integration, context model is introduced, and its characters are analyzed. The tree-like structure of inheritance among context model's classes is illustrated; The relationships of reference among them are also explained. Then, extensible markup language (XML) file is used to depict these classes. A four-tier framework of process integration has been established, in which model-view-controller pattern is designed to realize the separation between context model and its various views. The integration of applications is applied by the encapsulation of enterprise's business logic as distributed services. The prototype system for the design of air filter is applied in an institute.展开更多
A method of environment mapping using laser-based light detection and ranging (LIDAR) is proposed in this paper. This method not only has a good detection performance in a wide range of detection angles, but also fa...A method of environment mapping using laser-based light detection and ranging (LIDAR) is proposed in this paper. This method not only has a good detection performance in a wide range of detection angles, but also facilitates the detection of dynamic and hollowed-out obstacles. Essentially using this method, an improved clustering algorithm based on fast search and discovery of density peaks (CBFD) is presented to extract various obstacles in the environment map. By comparing with other cluster algorithms, CBFD can obtain a favorable number of clusterings automatically. Furthermore, the experiments show that CBFD is better and more robust in functionality and performance than the K-means and iterative self-organizing data analysis techniques algorithm (ISODATA).展开更多
Context-awareness enhances human-centric, intelligent behavior in a smart environment; however context-awareness is not widely used due to the lack of effective infrastructure to support context-aware applications. Th...Context-awareness enhances human-centric, intelligent behavior in a smart environment; however context-awareness is not widely used due to the lack of effective infrastructure to support context-aware applications. This paper presents an agent-based middleware for providing context-aware services for smart spaces to afford effective support for context acquisition, representation, interpretation, and utilization to applications. The middleware uses a formal context model, which combines first order probabilistic logic (FOPL) and web ontology language (OWL) ontologies, to provide a common understanding of contextual information to facilitate context modeling and reasoning about imperfect and ambiguous contextual information and to enable context knowledge sharing and reuse. A context inference mechanism based on an extended Bayesian network approach is used to enable automated reactive and deductive reasoning. The middleware is used in a case study in a smart classroom, and performance evaluation result shows that the context reasoning algorithm is good for non-time-critical applications and that the complexity is highly sensitive to the size of the context dataset.展开更多
Context modelling involves a) characterizing a situation with related information, and b) dealing and stor- ing the information in a computer-understandable form. It is the keystone to enable a system to possess the...Context modelling involves a) characterizing a situation with related information, and b) dealing and stor- ing the information in a computer-understandable form. It is the keystone to enable a system to possess the perception ca- pacity and adapt its functionality properly for different situa- tions. However, a context model focusing on the characteris- tics of work-based learning is not well studied by pioneering researchers. For addressing this issue, in this work we firstly analyze several existing context models to identify the essen- tials of context modelling, whereby a hierarchical ontology context model is proposed to characterize work-based learn- ing. Subsequently, we present the application of the proposed model in work-based learning scenario to provide adapted learning supports to professionals. Hence, this work has sig- nificance in both theory and practice.展开更多
Detecting and using bursty pattems to analyze text streams has been one of the fundamental approaches in many temporal text mining applications. So far, most existing studies have focused on developing methods to dete...Detecting and using bursty pattems to analyze text streams has been one of the fundamental approaches in many temporal text mining applications. So far, most existing studies have focused on developing methods to detect bursty features based purely on term frequency changes. Few have taken the semantic contexts of bursty features into consideration, and as a result the detected bursty features may not always be interesting and can be hard to interpret. In this article, we propose to model the contexts of bursty features using a language modeling approach. We propose two methods to estimate the context language models based on sentence-level context and document-level context. We then propose a novel topic diversity-based metric using the context models to find newsworthy bursty features. We also propose to use the context models to automatically assign meaningful tags to bursty features. Using a large corpus of news articles, we quantitatively show that the proposed context language models for bursty features can effectively help rank bursty features based on their newsworthiness and to assign meaningful tags to annotate bursty features. We also use two example text mining applications to qualitatively demonstrate the usefulness of bursty feature ranking and tagging.展开更多
As an elegant generalization of wavelet transform, wavelet packet (WP) provides an effective representation tool for adaptive waveform analysis. Recent work shows that image-coding methods based on WP decomposition ...As an elegant generalization of wavelet transform, wavelet packet (WP) provides an effective representation tool for adaptive waveform analysis. Recent work shows that image-coding methods based on WP decomposition can achieve significant gain over those based on a usual wavelet transform. However, most of the work adopts a tree-structured quantization scheme, which is a successful technique for wavelet image coding, but not appropriate for WP subbands. This paper presents an image-coding algorithm based on a rate-distortion optimized wavelet packet decomposition and on an intraband block-partitioning scheme. By encoding each WP subband separately with the block-partitioning algorithm and the JPEG2000 context modeling, the proposed algorithm naturally avoids the difficulty in defining parent-offspring relationships for the WP coefficients, which has to be faced when adopting the tree-structured quanUzation scheme. The experimental results show that the proposed algorithm significantly outperforms SPIHT and JPEG2000 schemes and also surpasses state-of-the-art WP image coding algorithms, in terms of both PSNR and visual quality.展开更多
文摘This paper proposes a method to recognize human-object interactions by modeling context between human actions and interacted objects.Human-object interaction recognition is a challenging task due to severe occlusion between human and objects during the interacting process.Since that human actions and interacted objects provide strong context information,i.e.some actions are usually related to some specific objects,the accuracy of recognition is significantly improved for both of them.Through the proposed method,both global and local temporal features from skeleton sequences are extracted to model human actions.In the meantime,kernel features are utilized to describe interacted objects.Finally,all possible solutions from actions and objects are optimized by modeling the context between them.The results of experiments demonstrate the effectiveness of our method.
基金National Defense Science Foundation of China (No.B0920060901)
文摘Process integration is the important aspect of product development process. The recent researches focus on project management, workflow management and process modeling. Based on the analysis of the process, product development process is divided into three levels according to different grains from macroscopy to microcosm. Our research concentrate on the workflow and the free-grained design process. According to the need of representing the data and the relationships among them for process integration, context model is introduced, and its characters are analyzed. The tree-like structure of inheritance among context model's classes is illustrated; The relationships of reference among them are also explained. Then, extensible markup language (XML) file is used to depict these classes. A four-tier framework of process integration has been established, in which model-view-controller pattern is designed to realize the separation between context model and its various views. The integration of applications is applied by the encapsulation of enterprise's business logic as distributed services. The prototype system for the design of air filter is applied in an institute.
基金Supported by the National Natural Science Foundation of China(61103157)
文摘A method of environment mapping using laser-based light detection and ranging (LIDAR) is proposed in this paper. This method not only has a good detection performance in a wide range of detection angles, but also facilitates the detection of dynamic and hollowed-out obstacles. Essentially using this method, an improved clustering algorithm based on fast search and discovery of density peaks (CBFD) is presented to extract various obstacles in the environment map. By comparing with other cluster algorithms, CBFD can obtain a favorable number of clusterings automatically. Furthermore, the experiments show that CBFD is better and more robust in functionality and performance than the K-means and iterative self-organizing data analysis techniques algorithm (ISODATA).
基金Supported by the Basic Research Foundation of Tsinghua Na-tional Laboratory for Information Science and Technology (TNList)the National High-Tech Research and Development (863) Program of China (No. 2006AA01Z198)
文摘Context-awareness enhances human-centric, intelligent behavior in a smart environment; however context-awareness is not widely used due to the lack of effective infrastructure to support context-aware applications. This paper presents an agent-based middleware for providing context-aware services for smart spaces to afford effective support for context acquisition, representation, interpretation, and utilization to applications. The middleware uses a formal context model, which combines first order probabilistic logic (FOPL) and web ontology language (OWL) ontologies, to provide a common understanding of contextual information to facilitate context modeling and reasoning about imperfect and ambiguous contextual information and to enable context knowledge sharing and reuse. A context inference mechanism based on an extended Bayesian network approach is used to enable automated reactive and deductive reasoning. The middleware is used in a case study in a smart classroom, and performance evaluation result shows that the context reasoning algorithm is good for non-time-critical applications and that the complexity is highly sensitive to the size of the context dataset.
文摘Context modelling involves a) characterizing a situation with related information, and b) dealing and stor- ing the information in a computer-understandable form. It is the keystone to enable a system to possess the perception ca- pacity and adapt its functionality properly for different situa- tions. However, a context model focusing on the characteris- tics of work-based learning is not well studied by pioneering researchers. For addressing this issue, in this work we firstly analyze several existing context models to identify the essen- tials of context modelling, whereby a hierarchical ontology context model is proposed to characterize work-based learn- ing. Subsequently, we present the application of the proposed model in work-based learning scenario to provide adapted learning supports to professionals. Hence, this work has sig- nificance in both theory and practice.
基金Acknowledgements The authors thank the anonymous reviewers for their valuable and constructive comments. The work was partially supported by the National Natural Science Foundation of China (Grant No. 61502502), the National Basic Research Program (973 Program) of China (2014CB340403), Beijing Natural Science Foundation (4162032), and the Open Fund of Beijing Key Laboratory on Integration and Analysis of Large-scale Stream Data, North China University of Technology, China.
文摘Detecting and using bursty pattems to analyze text streams has been one of the fundamental approaches in many temporal text mining applications. So far, most existing studies have focused on developing methods to detect bursty features based purely on term frequency changes. Few have taken the semantic contexts of bursty features into consideration, and as a result the detected bursty features may not always be interesting and can be hard to interpret. In this article, we propose to model the contexts of bursty features using a language modeling approach. We propose two methods to estimate the context language models based on sentence-level context and document-level context. We then propose a novel topic diversity-based metric using the context models to find newsworthy bursty features. We also propose to use the context models to automatically assign meaningful tags to bursty features. Using a large corpus of news articles, we quantitatively show that the proposed context language models for bursty features can effectively help rank bursty features based on their newsworthiness and to assign meaningful tags to annotate bursty features. We also use two example text mining applications to qualitatively demonstrate the usefulness of bursty feature ranking and tagging.
基金the Major State Basic Research Development Program(973 Program)(Grant No.2004CB318005)
文摘As an elegant generalization of wavelet transform, wavelet packet (WP) provides an effective representation tool for adaptive waveform analysis. Recent work shows that image-coding methods based on WP decomposition can achieve significant gain over those based on a usual wavelet transform. However, most of the work adopts a tree-structured quantization scheme, which is a successful technique for wavelet image coding, but not appropriate for WP subbands. This paper presents an image-coding algorithm based on a rate-distortion optimized wavelet packet decomposition and on an intraband block-partitioning scheme. By encoding each WP subband separately with the block-partitioning algorithm and the JPEG2000 context modeling, the proposed algorithm naturally avoids the difficulty in defining parent-offspring relationships for the WP coefficients, which has to be faced when adopting the tree-structured quanUzation scheme. The experimental results show that the proposed algorithm significantly outperforms SPIHT and JPEG2000 schemes and also surpasses state-of-the-art WP image coding algorithms, in terms of both PSNR and visual quality.