Networked robotics involves a collection of robots working together to perform complex tasks, suc... more Networked robotics involves a collection of robots working together to perform complex tasks, such as search and rescue task in disaster management. Because such tasks are beyond the capacity of a single powerful robot, networked robotics has been widely researched. However, the modes of cooperation in traditional networked robotics have been restricted by the inherent physical constraint that all computations are performed in the robotic network, with knowledge sharing being limited to the collective storage in the network. Cloud robotics, which allows robots to benefit from the rich storage, computation, and communication resources of modern data centers, is widely accepted as a promising approach to efficient robot cooperation in applications, such as disaster management. In this paper, we study robotic cooperation in cloud robotics. We first give a conceptual view of the nature of this cooperation. We then propose three novel robotic cooperation frameworks for cloud robotics: robotic knowledge sharing cooperation, robotic physical-task cooperation, and robotic computation task cooperation. Finally, we identify several critical challenges, and illustrate the potential benefits of robotic cooperation in cloud robotics. INDEX TERMS Cloud robotics, multi-robot system, robot cooperation, quality of service.
IPSJ Transactions on Computer Vision and Applications, 2010
A two-dimensional continuous dynamic programming (2DCDP) method is proposed for two-dimensional (... more A two-dimensional continuous dynamic programming (2DCDP) method is proposed for two-dimensional (2D) spotting recognition of images. Spotting recognition is the simultaneous segmentation and recognition of an image by optimal pixel matching between a reference image and an input image. The proposed method performs optimal pixel-wise image matching and 2D pixel alignment, which are not available in conventional algorithms. Experimental results show that 2DCDP precisely matches the pixels of nonlinearly deformed images.
Speech and Song Search on the Web: System Design and Implementation
7th IEEE International Conference on Computer and Information Technology (CIT 2007), 2007
ABSTRACT This paper proposes a novel search system for speech and song segments. The amount of ac... more ABSTRACT This paper proposes a novel search system for speech and song segments. The amount of accumulated video data in the World Wide Web is expanding and its content is varied. Video content includes natural voices and singing voices, and these differ in their phoneme lengths. Our system uses frame-wise phoneme recognition and Continuous Dynamic Programming (CDP). First, each target and query waveform is divided into fixed short-time frames; second, each frame of the waveform is used to estimate a phoneme label using Bayes estimation; third, the query sequences of phoneme labels are searched from target sequences by time-robustness CDP; and, finally, this system gets candidate answers. This method is robust along the time dimension, and thus has a great advantage for natural voice as well as song. This paper also introduces an implementation of this system, which is published on the Web, as a secondary search engine for Youtube data.
Fast spotter: An approximation algorithm for continuous dynamic programming
2008 8th IEEE International Conference on Computer and Information Technology, 2008
ABSTRACT Spotting recognition is the simultaneous realization of both recognition and segmentatio... more ABSTRACT Spotting recognition is the simultaneous realization of both recognition and segmentation. It is able to extract suitable information from an input dataset satisfying a query, and has developed into a research topic known as word spotting that uses dynamic programming or hidden Markov models. Continuous dynamic programming (CDP) is a promising method for spotting recognition applied to sequential patterns. However, the computational burden for conducting a retrieval task using CDP increases as O(JIP), where I is the input length, J is the reference length and P is the number of paths. This paper proposes a faster nonlinear spotting method like CDP, called fast spotter (FS). FS is regarded as an approximation of CDP using A* search. FS reduces the computational burden to O(IP log2 J) in the best case and executes in around half the time with an experimental dataset, enabling it to realize a large-scale speech retrieval system.
Feature detection of electrical feeder lines with galloping motion
2008 8th IEEE International Conference on Computer and Information Technology, 2008
ABSTRACT To detect and observe the location and angle of electrical feeder lines in galloping mov... more ABSTRACT To detect and observe the location and angle of electrical feeder lines in galloping movies, the observer must recognize the relation of two red balls acting as spacers for pairs of lines. This research proposes and develops a system to detect these balls using color recognition in image processing. Our experiments, show that this system is successful in finding feeder lines and recognizing the angles of the lines for almost all cases. Additionally, the system has the advantage that it can interpolate for missed frames during recognition. However, some movies have color problems.
Clustering and Spherical Visualization of Web Services
2013 IEEE International Conference on Services Computing, 2013
ABSTRACT Web service clustering is one of a very efficient approach to discover Web services effi... more ABSTRACT Web service clustering is one of a very efficient approach to discover Web services efficiently. Current clustering approaches use traditional clustering algorithms such as agglomerative as the clustering algorithm. The algorithms have not provided visualization of service clusters that gives inspiration for a specific domain from visual feedback and failed to achieve higher noise isolation. Furthermore iterative steps of algorithms consider about the similarity of limited number of services such as similarity of cluster centers. This leads to reduce the cluster performance. In this paper we apply a spatial clustering technique called the Associated Keyword Space(ASKS) which is effective for noisy data and projected clustering result from a three-dimensional (3D) sphere to a two dimensional(2D) spherical surface for 2D visualization. One main issue, which affects to the performance of ASKS algorithm is creating the affinity matrix. We use semantic similarity values between services as the affinity values. Most of the current clustering approaches use similarity distance measurement such as keyword, ontology and information-retrieval-based methods. These approaches have problem of short of high quality ontology and loss of semantic information. In this paper, we calculate the service similarity by using hybrid term similarity method which uses ontology learning and information retrieval. Experimental results show our clustering approach is able to plot similar services into same area and aid to search Web services by visualization of the service data on a spherical surface.
Clustering and Spherical Visualization of Web Services
Web service clustering is one of a very efficient approach to discover Web services efficiently. ... more Web service clustering is one of a very efficient approach to discover Web services efficiently. Current clustering approaches use traditional clustering algorithms such as agglomerative as the clustering algorithm. The algorithms have not provided visualization of service clusters that gives inspiration for a specific domain from visual feedback and failed to achieve higher noise isolation. Furthermore iterative steps of algorithms consider about the similarity of limited number of services such as similarity of cluster centers. This leads to reduce the cluster performance. In this paper we apply a spatial clustering technique called the Associated Keyword Space(ASKS) which is effective for noisy data and projected clustering result from a three-dimensional (3D) sphere to a two dimensional(2D) spherical surface for 2D visualization. One main issue, which affects to the performance of ASKS algorithm is creating the affinity matrix. We use semantic similarity values between services ...
IPSJ Transactions on Computer Vision and Applications
A two-dimensional continuous dynamic programming (2DCDP) method is proposed for two-dimensional (... more A two-dimensional continuous dynamic programming (2DCDP) method is proposed for two-dimensional (2D) spotting recognition of images. Spotting recognition is the simultaneous segmentation and recognition of an image by optimal pixel matching between a reference image and an input image. The proposed method performs optimal pixel-wise image matching and 2D pixel alignment, which are not available in conventional algorithms. Experimental results show that 2DCDP precisely matches the pixels of nonlinearly deformed images.
Spherical visualization of image data with clustering
4th International Conference on Awareness Science and Technology, 2012
This paper proposes to aid the search for images by visualization of the image data on a spherica... more This paper proposes to aid the search for images by visualization of the image data on a spherical surface. Many photographs were lost in the Tohoku tsunami, and those that were eventually found are now being scanned. However, the owners of the lost photographs are finding it difficult to search for their images within a large set of scanned images that contain no additional information. In this paper, we apply a spatial clustering technique called the Associated Keyword Space (ASKS) projected from a threedimensional (3D) sphere to a two-dimensional (2D) spherical surface for 2D visualization. ASKS supports clustering, and therefore, we construct an image search system in which similar images are clustered. In this system, similar images are identified by color inspection and by having similar characteristics. In this way, the system is able to support the search for images from within a huge number of images.
Linked Data-Based Service Publication for Service Clustering
Lecture Notes in Electrical Engineering, 2014
ABSTRACT In this paper, we propose an approach to publish services based on Linked data principle... more ABSTRACT In this paper, we propose an approach to publish services based on Linked data principles and discover services by service cluster with visualization for reducing the using thresholds. First, we propose Linked social service which is published on the open web by following Linked data principles with social link, then, a spatial clustering algorithm is proposed to enable visualization for reducing the using thresholds. Finally, experiment is conducted to show the effectiveness of our proposed approach.
Extracting Objects by Clustering of Full Pixel Trajectories
We propose a novel method for the segmentation of objects and the extraction of motion features f... more We propose a novel method for the segmentation of objects and the extraction of motion features for moving objects in video data. The method adopts an algorithm called two-dimensional continuous dynamic programming (2DCDP) for extracting pixel-wise trajectories. A clustering algorithm is applied to a set of pixel trajectories to determine objects each of which corresponds to a trajectory cluster. We
Networked robotics involves a collection of robots working together to perform complex tasks, suc... more Networked robotics involves a collection of robots working together to perform complex tasks, such as search and rescue task in disaster management. Because such tasks are beyond the capacity of a single powerful robot, networked robotics has been widely researched. However, the modes of cooperation in traditional networked robotics have been restricted by the inherent physical constraint that all computations are performed in the robotic network, with knowledge sharing being limited to the collective storage in the network. Cloud robotics, which allows robots to benefit from the rich storage, computation, and communication resources of modern data centers, is widely accepted as a promising approach to efficient robot cooperation in applications, such as disaster management. In this paper, we study robotic cooperation in cloud robotics. We first give a conceptual view of the nature of this cooperation. We then propose three novel robotic cooperation frameworks for cloud robotics: robotic knowledge sharing cooperation, robotic physical-task cooperation, and robotic computation task cooperation. Finally, we identify several critical challenges, and illustrate the potential benefits of robotic cooperation in cloud robotics. INDEX TERMS Cloud robotics, multi-robot system, robot cooperation, quality of service.
IPSJ Transactions on Computer Vision and Applications, 2010
A two-dimensional continuous dynamic programming (2DCDP) method is proposed for two-dimensional (... more A two-dimensional continuous dynamic programming (2DCDP) method is proposed for two-dimensional (2D) spotting recognition of images. Spotting recognition is the simultaneous segmentation and recognition of an image by optimal pixel matching between a reference image and an input image. The proposed method performs optimal pixel-wise image matching and 2D pixel alignment, which are not available in conventional algorithms. Experimental results show that 2DCDP precisely matches the pixels of nonlinearly deformed images.
Speech and Song Search on the Web: System Design and Implementation
7th IEEE International Conference on Computer and Information Technology (CIT 2007), 2007
ABSTRACT This paper proposes a novel search system for speech and song segments. The amount of ac... more ABSTRACT This paper proposes a novel search system for speech and song segments. The amount of accumulated video data in the World Wide Web is expanding and its content is varied. Video content includes natural voices and singing voices, and these differ in their phoneme lengths. Our system uses frame-wise phoneme recognition and Continuous Dynamic Programming (CDP). First, each target and query waveform is divided into fixed short-time frames; second, each frame of the waveform is used to estimate a phoneme label using Bayes estimation; third, the query sequences of phoneme labels are searched from target sequences by time-robustness CDP; and, finally, this system gets candidate answers. This method is robust along the time dimension, and thus has a great advantage for natural voice as well as song. This paper also introduces an implementation of this system, which is published on the Web, as a secondary search engine for Youtube data.
Fast spotter: An approximation algorithm for continuous dynamic programming
2008 8th IEEE International Conference on Computer and Information Technology, 2008
ABSTRACT Spotting recognition is the simultaneous realization of both recognition and segmentatio... more ABSTRACT Spotting recognition is the simultaneous realization of both recognition and segmentation. It is able to extract suitable information from an input dataset satisfying a query, and has developed into a research topic known as word spotting that uses dynamic programming or hidden Markov models. Continuous dynamic programming (CDP) is a promising method for spotting recognition applied to sequential patterns. However, the computational burden for conducting a retrieval task using CDP increases as O(JIP), where I is the input length, J is the reference length and P is the number of paths. This paper proposes a faster nonlinear spotting method like CDP, called fast spotter (FS). FS is regarded as an approximation of CDP using A* search. FS reduces the computational burden to O(IP log2 J) in the best case and executes in around half the time with an experimental dataset, enabling it to realize a large-scale speech retrieval system.
Feature detection of electrical feeder lines with galloping motion
2008 8th IEEE International Conference on Computer and Information Technology, 2008
ABSTRACT To detect and observe the location and angle of electrical feeder lines in galloping mov... more ABSTRACT To detect and observe the location and angle of electrical feeder lines in galloping movies, the observer must recognize the relation of two red balls acting as spacers for pairs of lines. This research proposes and develops a system to detect these balls using color recognition in image processing. Our experiments, show that this system is successful in finding feeder lines and recognizing the angles of the lines for almost all cases. Additionally, the system has the advantage that it can interpolate for missed frames during recognition. However, some movies have color problems.
Clustering and Spherical Visualization of Web Services
2013 IEEE International Conference on Services Computing, 2013
ABSTRACT Web service clustering is one of a very efficient approach to discover Web services effi... more ABSTRACT Web service clustering is one of a very efficient approach to discover Web services efficiently. Current clustering approaches use traditional clustering algorithms such as agglomerative as the clustering algorithm. The algorithms have not provided visualization of service clusters that gives inspiration for a specific domain from visual feedback and failed to achieve higher noise isolation. Furthermore iterative steps of algorithms consider about the similarity of limited number of services such as similarity of cluster centers. This leads to reduce the cluster performance. In this paper we apply a spatial clustering technique called the Associated Keyword Space(ASKS) which is effective for noisy data and projected clustering result from a three-dimensional (3D) sphere to a two dimensional(2D) spherical surface for 2D visualization. One main issue, which affects to the performance of ASKS algorithm is creating the affinity matrix. We use semantic similarity values between services as the affinity values. Most of the current clustering approaches use similarity distance measurement such as keyword, ontology and information-retrieval-based methods. These approaches have problem of short of high quality ontology and loss of semantic information. In this paper, we calculate the service similarity by using hybrid term similarity method which uses ontology learning and information retrieval. Experimental results show our clustering approach is able to plot similar services into same area and aid to search Web services by visualization of the service data on a spherical surface.
Clustering and Spherical Visualization of Web Services
Web service clustering is one of a very efficient approach to discover Web services efficiently. ... more Web service clustering is one of a very efficient approach to discover Web services efficiently. Current clustering approaches use traditional clustering algorithms such as agglomerative as the clustering algorithm. The algorithms have not provided visualization of service clusters that gives inspiration for a specific domain from visual feedback and failed to achieve higher noise isolation. Furthermore iterative steps of algorithms consider about the similarity of limited number of services such as similarity of cluster centers. This leads to reduce the cluster performance. In this paper we apply a spatial clustering technique called the Associated Keyword Space(ASKS) which is effective for noisy data and projected clustering result from a three-dimensional (3D) sphere to a two dimensional(2D) spherical surface for 2D visualization. One main issue, which affects to the performance of ASKS algorithm is creating the affinity matrix. We use semantic similarity values between services ...
IPSJ Transactions on Computer Vision and Applications
A two-dimensional continuous dynamic programming (2DCDP) method is proposed for two-dimensional (... more A two-dimensional continuous dynamic programming (2DCDP) method is proposed for two-dimensional (2D) spotting recognition of images. Spotting recognition is the simultaneous segmentation and recognition of an image by optimal pixel matching between a reference image and an input image. The proposed method performs optimal pixel-wise image matching and 2D pixel alignment, which are not available in conventional algorithms. Experimental results show that 2DCDP precisely matches the pixels of nonlinearly deformed images.
Spherical visualization of image data with clustering
4th International Conference on Awareness Science and Technology, 2012
This paper proposes to aid the search for images by visualization of the image data on a spherica... more This paper proposes to aid the search for images by visualization of the image data on a spherical surface. Many photographs were lost in the Tohoku tsunami, and those that were eventually found are now being scanned. However, the owners of the lost photographs are finding it difficult to search for their images within a large set of scanned images that contain no additional information. In this paper, we apply a spatial clustering technique called the Associated Keyword Space (ASKS) projected from a threedimensional (3D) sphere to a two-dimensional (2D) spherical surface for 2D visualization. ASKS supports clustering, and therefore, we construct an image search system in which similar images are clustered. In this system, similar images are identified by color inspection and by having similar characteristics. In this way, the system is able to support the search for images from within a huge number of images.
Linked Data-Based Service Publication for Service Clustering
Lecture Notes in Electrical Engineering, 2014
ABSTRACT In this paper, we propose an approach to publish services based on Linked data principle... more ABSTRACT In this paper, we propose an approach to publish services based on Linked data principles and discover services by service cluster with visualization for reducing the using thresholds. First, we propose Linked social service which is published on the open web by following Linked data principles with social link, then, a spatial clustering algorithm is proposed to enable visualization for reducing the using thresholds. Finally, experiment is conducted to show the effectiveness of our proposed approach.
Extracting Objects by Clustering of Full Pixel Trajectories
We propose a novel method for the segmentation of objects and the extraction of motion features f... more We propose a novel method for the segmentation of objects and the extraction of motion features for moving objects in video data. The method adopts an algorithm called two-dimensional continuous dynamic programming (2DCDP) for extracting pixel-wise trajectories. A clustering algorithm is applied to a set of pixel trajectories to determine objects each of which corresponds to a trajectory cluster. We
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