At present, in the field of pixel-level image fusion, researchers tend to treat each pixel independently, which destroys the relationship between the images to be fused. In view of this defects, this paper aims to pro...
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This paper focuses on an application motion control of avatar and accuracy measurements using Kinect. The development of this application has used C++ Builder as a compiler and libraries to connect with Kinect and sho...
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Indoor localization is a popular topic because of the poor performance of GPS in the indoor environment. This paper has provided a new method to achieve the goal of indoor localization. Combining the usage of posture ...
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ISBN:
(纸本)9781467382182
Indoor localization is a popular topic because of the poor performance of GPS in the indoor environment. This paper has provided a new method to achieve the goal of indoor localization. Combining the usage of posture sensors with the Radio Frequency Identification (RFID) technology, we solved the problem of plentiful tags in the traditional RFID indoor localization. The relative localization subsystem is based on posture sensors and the absolute localization subsystem is based on RFID. A set-membership theory based data fusion algorithm is proposed to fuse the data of relative localization and absolute localization. Experimental results show that the proposed data fusion algorithm could significantly reduce the accumulated error of our indoor localization system.
Here we report a controllable four DNA sub-tiles, self-assembling into 4-arm DNA tiles, under control of a DNA strand displacement based on DNA sequential circuit. The motif is encoded, compiled and simulated successi...
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A scheme is proposed to hide data in images based on a prioritized ordering of the content of the host (or cover) image. A watermark embedding process uses the watermark strength to determine the ordering of the 16 re...
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Automatic human action recognition is a core functionality of systems for video surveillance and human-object interaction. However, the diverse nature of human actions and the noisy nature of most video content make i...
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ISBN:
(纸本)9781479947607
Automatic human action recognition is a core functionality of systems for video surveillance and human-object interaction. However, the diverse nature of human actions and the noisy nature of most video content make it difficult to achieve effective human action recognition. To overcome the aforementioned problems, Sparse Representation (SR) has recently attracted substantial research attention. However, although SR-based approaches have proven to be reasonably effective, the computational complexity of the testing stage prohibits their usage by applications requiring support for real-time operation and a vast number of human action classes. In this paper, we propose a novel method for human action recognition, leveraging coarse-to-fine sparse representations that have been obtained through dictionary sub-sampling. Comparative experimental results obtained for the UCF50 dataset demonstrate that the proposed method is able to achieve efficient human action recognition, at no substantial loss in recognition accuracy.
This paper focuses on an application motion control of avatar and accuracy measurements using Kinect. The development of this application has used C++ Builder as a compiler and libraries to connect with Kinect and sho...
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This paper focuses on an application motion control of avatar and accuracy measurements using Kinect. The development of this application has used C++ Builder as a compiler and libraries to connect with Kinect and show 3D virtual world and avatars. OpenNI library is to detect a depth image while NITE Primesense library is to connect with Kinect, and Chai3D to display virtual worlds and avatar (human motion models). The tests to measure the application performance consist of 2D-3D angular measurements and time delay measurements on motions between avatar and a controller. The paired T-Test results on angular measurements showed that 2D and 3D angular measurements can be substitutable depended on the positions between Kinect and a controller. Furthermore, comparisons by ratio between the time difference showed varies due to the motion factors, the number of vertices and the distance between Kinect and the controller.
The discrete-time double-integrator consensus and rendezvous problems are both addressed for distributed multiagent systems with directed switching topologies and input *** develop model predictive control algorithms ...
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ISBN:
(纸本)9781479947249
The discrete-time double-integrator consensus and rendezvous problems are both addressed for distributed multiagent systems with directed switching topologies and input *** develop model predictive control algorithms to achieve stable consensus or rendezvous provided that the proximity nets always have a directed spanning tree and the sampling period is sufficiently ***,the control horizon is extended to larger than one as well,which endows sufficient degrees of freedom to facilitate controller *** simulations are finally conducted to show the effectiveness of the control algorithms.
Robot-assisted partial nephrectomy (RAPN) is a minimally invasive surgery for the treatment of renal cell carcinoma that consists of removing the portion of the kidney that contains the tumor. To plan the resection, s...
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Robot-assisted partial nephrectomy (RAPN) is a minimally invasive surgery for the treatment of renal cell carcinoma that consists of removing the portion of the kidney that contains the tumor. To plan the resection, surgeons rely on preoperative scans of the patient. However, at surgery time, the shape of abdominal organs differ from these images due to factors such as patient position, insufflation and manipulation with surgical instruments. In this work, we focus on the simulation of kidney deformation due to an external pressure load, e.g. during insufflation, to provide a better estimation of the tumor mass position that is particularly important to plan resection with proper margins. The CT scans of ex vivo lamb kidneys with artificial tumors and fiducials are acquired in absence of external pressure load. From these images, 3D tetra-hedral meshes of kidney parenchyma and tumor, as well as a triangular mesh of the capsule, are extracted and then used along with a soft tissue biomechanical model to simulate deformations under additional external pressure load. A second CT scan of the same kidneys under real pressure load are acquired as a reference to evaluate the advantage of simulating deformations over using the first CT scan without external pressure load. Results show that the biomechanical simulation improves by 29% the tumor localization.
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