Wearable device with an ego-centric camera would be the next generation device for human-computer interaction such as robot *** gesture is a natural way of egocentric human-computer *** this paper, we present an ego-c...
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Wearable device with an ego-centric camera would be the next generation device for human-computer interaction such as robot *** gesture is a natural way of egocentric human-computer *** this paper, we present an ego-centric multi-stage hand gesture analysis pipeline for robot control which works robustly in the unconstrained environment with varying *** particular, we first propose an adaptive color and contour based hand segmentation method to segment hand region from the egocentric *** then propose a convex U-shaped curve detection algorithm to precisely detect positions of *** parallelly, we utilize the convolutional neural networks to recognize hand *** on these techniques, we combine most information of hand to control the robot and develop a hand gesture analysis system on an i Phone and a robot arm platform to validate its *** result demonstrates that our method works perfectly on controlling the robot arm by hand gesture in real time.
Temporal alignment aligns two temporal sequences and is quite challenging due to drastic differences among temporal sequences and source data from different views. Canonical time warping (CTW) has shown great potentia...
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ISBN:
(纸本)9781509006212
Temporal alignment aligns two temporal sequences and is quite challenging due to drastic differences among temporal sequences and source data from different views. Canonical time warping (CTW) has shown great potential in temporal alignment tasks because it can reduce data redundancy by transforming high-dimensional data to a lower-dimensional subspace via canonical correlation analysis (CCA). However, CTW cannot uncover the underlying nonlinear structure embedded in the dataset. In this paper, we propose an autoencoder regularized canonical time warping method (AECTW) to overcome this drawback. Specifically, AECTW enhances lower-dimensional representation of each sequence by incorporating an autoencoder regularization, meanwhile reveals the nonlinear structure of features by explicit nonlinear transformation. By these strategies, AECTW significantly boosts CTW in temporal alignment tasks. Experiments on both synthetic data and two practical human action datasets demonstrate that AECTW outperforms the representative DTW-based methods.
This paper investigates the problem of maximizing uniform multicast throughput (MUMT) for multi-channel dense wireless sensor networks, where all nodes locate within one-hop transmission range and can communicate with...
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As the big data era is coming, it brings new challenges to the massive data processing. A combination of GPU and CPU on chip is the trend to release the pressure of large scale computing. We found that there are diffe...
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In this paper, we present the Tianhe-2 interconnect network and message passing services. We describe the architecture of the router and network interface chips, and highlight a set of hardware and software features e...
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In this paper, we present the Tianhe-2 interconnect network and message passing services. We describe the architecture of the router and network interface chips, and highlight a set of hardware and software features effectively supporting high performance communications, ranging over remote direct memory access, collective optimization, hardwareenable reliable end-to-end communication, user-level message passing services, etc. Measured hardware performance results are also presented.
As The integration of Physical space and cyberspace, the large-scale data distributing to diversification terminal which is geographical distribution of mass has become a huge challenge. When the data size can't b...
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As The integration of Physical space and cyberspace, the large-scale data distributing to diversification terminal which is geographical distribution of mass has become a huge challenge. When the data size can't be processed by the technology for traditional scope, how to deal with the user quality of service and efficient use of system resources has become an important issue of concern, with the resources becoming limited. This paper presents a data-driven mechanism for large-scale data distribution which is consists of four core part of the data production, data collection and pre-processing, data analysis engine, data consumption, aims to excavate the valuable information to improve the efficiency of resource use and accurate fault location for the Large-scale data distribution system. At the same time, this paper studies the resource scheduling optimization with analyzing data driven for the system behavior and Fault location with analyzing data-driven environment, which proves the effectiveness for the operation of the Large-scale data distribution system optimization by the data-driven working.
Determinism is very useful to multithreaded programs in debugging, testing, etc. Many deterministic ap- proaches have been proposed, such as deterministic multithreading （DMT） and deterministic replay. However, thes...
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Determinism is very useful to multithreaded programs in debugging, testing, etc. Many deterministic ap- proaches have been proposed, such as deterministic multithreading （DMT） and deterministic replay. However, these sys- tems either are inefficient or target a single purpose, which is not flexible. In this paper, we propose an efficient and flexible deterministic framework for multithreaded programs. Our framework implements determinism in two steps： relaxed determinism and strong determinism. Relaxed determinism solves data races eificiently by using a proper weak memory consistency model. After that, we implement strong determinism by solving lock contentions deterministically. Since we can apply different approaches for these two steps independently, our framework provides a spectrum of deterministic choices, including nondeterministic system （fast）, weak deterministic system （fast and conditionally deterministic）, DMT system, and deternfinistic replay system. Our evaluation shows that the DMT configuration of this framework could even outperform a state-of-the-art DMT system.
Semi-supervised learning (SSL) utilizes plenty of unlabeled examples to boost the performance of learning from limited labeled examples. Due to its great discriminant power, SSL has been widely applied to various real...
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Detecting concurrency bugs is becoming increasingly important. Many pattern-based concurrency bug detectors focus on the specific types of interleavings that are correlated to concurrency bugs. To detect multiple type...
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One of the most significant challenges introduced by routing protocol in mobile networks is coping with the unpredictable motion and the unreliable behaviour of mobile nodes. In this paper, we present a hierarchical r...
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