Wireless sensor networks (WSNs) have attracted a great deal of research due to their wide-range of potential applications. Sensor deployment and coverage problems are their important issues. This article briefly intro...
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The AAAI-11 workshop program was held Sunday and Monday, August 7-18, 2011, at the Hyatt Regency San Francisco in San Francisco, California USA. The AAAI-11 workshop program included 15 workshops covering a wide range...
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This paper describes a fully autonomous mobile urban robot-X1, which can perform multiple tasks autonomously in an unknown urban environment without human guidance, including mobile reconnaissance, target searching, a...
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This paper describes a fully autonomous mobile urban robot-X1, which can perform multiple tasks autonomously in an unknown urban environment without human guidance, including mobile reconnaissance, target searching, and object manipulation. The mission-oriented design, which allows reliability and extensibility of the robotic system, includes a high degree of modularity for both hardware and software architecture, and coordination between tasks. Our strategy specifically addresses fundamental issues such as autonomous navigation in unknown urban environments and vision-based object manipulation. All the functionalities have been proved effective in the real urban environments. The robot platform is being built to provide valuable experiences on autonomous roboticsresearch.
Camera handoff is a crucial step to generate a continuously tracked and consistently labeled trajectory of the object of interest in multi-camera surveillance systems. Most existing camera handoff algorithms concentra...
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Camera handoff is a crucial step to generate a continuously tracked and consistently labeled trajectory of the object of interest in multi-camera surveillance systems. Most existing camera handoff algorithms concentrate on data association, namely consistent labeling, where images of the same object are matched across different cameras. However, most real-time object tracking systems see a decrease in the system's frame rate as the number of tracked objects increases. To address this issue, we propose to incorporate an adaptive resource management mechanism into camera handoff. In so doing, cameras¿ resources can be dynamically allocated to multiple objects according to their priorities and hence the required minimum frame rate can be maintained. Experimental results illustrate that the proposed camera handoff algorithm is capable of maintaining a constant frame rate and of achieving a substantially improved handoff success rate by approximately 20% in comparison with the algorithm presented by Khan and Shah.
Spartacus is our robot entry in the 2005 AAAI Mobile Robot Challenge, making a robot attend the National Conference on Artificial Intelligence. Designing robots that are capable of interacting with humans in real-life...
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This paper presents the components and overall architecture of the ubiquitous robot (Ubibot) system developed to demonstrate ubiquitous robotics, a new paradigm for integrated services. The system has been developed o...
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This paper presents the components and overall architecture of the ubiquitous robot (Ubibot) system developed to demonstrate ubiquitous robotics, a new paradigm for integrated services. The system has been developed on the basis of the definition of the ubiquitous robot as that of encompassing the software robot Sobot, embedded robot Embot and the mobile robot Mobot. This tripartite partition, which independently manifests intelligence, perception and action, enables the abstraction of intelligence through the standardization of sensory data and motor or action commands. The Ubibot system itself is introduced along with its component subsystems of Embots, the position Embot, vision Embot and sound Embot, the Mobots of Mybot and HSR, the Sobot, Rity, a virtual pet modeled as an artificial creature, and finally the middleware which seamlessly enables interconnection between other components. Three kinds of experiments are devised to demonstrate the fundamental features, of calm sensing, context awareness and seamless service transcending the spatial limitations in the abilities of earlier generation personal robots. The experiments demonstrate the proof of concept of this powerful new paradigm which shows great promise.
In this paper a coarse-to-fine system framework for analyzing the head gesture is presented. We discuss several important modules from computervision aspects, including the pose-invariant face detection, face trackin...
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In this paper a coarse-to-fine system framework for analyzing the head gesture is presented. We discuss several important modules from computervision aspects, including the pose-invariant face detection, face tracking, pose determination and high-resolution image reconstruction for eye pupils detection. Visual cues using intensity images obtained from in-car cameras are explored. A pose-invariant face detection algorithm is used to get the initial face area; afterwards face tracking and validation step is proposed to segment the face region for pose determination. The algorithm is tested on the drivers images under natural driving conditions. Experimental results show that the algorithm is robust to the head pose changes as well as the illumination changes. In this system framework, we propose that when coarse analysis utilizing the head pose alone is not sufficient for driver's behavior analysis, a finer analysis based on the eye gaze tracking is used, which requires images with sufficient resolution. A novel super-resolution reconstruction algorithm is proposed to help reveal more facial details, so as to facilitate the pupil detection. Experiment on the synthesis data shows the effectiveness of the super-resolution reconstruction algorithm
A regression model in the tensorPCA subspace is proposed in this paper for face super-resolution reconstruction. An approximate conditional probability model is used for the tensor subspace coefficients and maximum-li...
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ISBN:
(纸本)0769525210
A regression model in the tensorPCA subspace is proposed in this paper for face super-resolution reconstruction. An approximate conditional probability model is used for the tensor subspace coefficients and maximum-likelihood estimator gives a linear regression model. The approximation is corrected by adding non-linear component from a RBF-type regressor. Experiments on face images from FERET database validate the algorithm. Although each projection coefficient is estimated by a local estimator, tensorPCA subspace analysis is still a global descriptor, which makes the algorithm have certain ability to deal with partially occluded images
We propose an approach to incorporate spatial information into the estimate of the entropy of an image by partitioning a high-dimensional space into regions over which a one-dimensional histogram can be indexed. This ...
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We propose an approach to incorporate spatial information into the estimate of the entropy of an image by partitioning a high-dimensional space into regions over which a one-dimensional histogram can be indexed. This approach obviates the need for the construction of high-dimensional histograms and makes no assumptions on the form of the high-dimensional probability mass function. We use this partitioned estimate of entropy to compute image similarity measures, useful in image registration, and we examine the convergence properties of the registration process
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