This paper presents an imaging method for 360-degree panoramic view based on four wide angle cameras. In order to complete the image mosaic, all the parameters such as focal length, principal point and distortion coef...
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This paper presents an imaging method for 360-degree panoramic view based on four wide angle cameras. In order to complete the image mosaic, all the parameters such as focal length, principal point and distortion coefficients, etc are calibrated by our proposed calibration toolbox. Then, our approach does not adopt the scheme which stitching all the images to the surrounding view after distortion correction. The proposed method directly calculates the mapping relationship between the wide-angle lens images and cylindrical projection images to generate lookup tables which can greatly simplifies the computation and reduces the loss of information in each image. Finally, panoramic image is composed by image registration and image fusion. Experimental results show that this method is valid.
This paper addresses the unimodal and hysteresis thresholding, where a pair of low and high thresholds is under investigation targeted with the unimodal image histogram. The novel bowstring is introduced to make an ac...
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Differential spatial modulation (DSM) is a newly proposed differential modulation technique tailored to spatial modulation (SM), which requires no channel state information (CSI) at the receiver. DSM can offer flexibl...
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ISBN:
(纸本)9781467364300
Differential spatial modulation (DSM) is a newly proposed differential modulation technique tailored to spatial modulation (SM), which requires no channel state information (CSI) at the receiver. DSM can offer flexible tradeoff between the reception reliability and the system complexity. In this paper, we are the first to study the adoption of DSM in a dual-hop amplify-and-forward (AF) relaying system, which consists of a two-antenna source, a single-antenna relay, and a single-antenna destination, so as to reduce the burden of channel tracking on both the relay and the destination. We derive a general upper bound on the average bit error probability (ABEP) achieved by the system. Moreover, an exact closed-form ABEP expression and the asymptotic result are provided for BPSK signaling in Rayleigh fading environment. The same system setup with the adoption of SM at the source is chosen as a benchmark for performance comparisons. Simulation results validate the analysis and reveal a 3dB signal-to-noise power ratio (SNR) penalty of the considered system compared with the benchmark.
This paper considers the cooperative output regulation problem for linear multi-agent systems with a directed communication graph, heterogeneous linear agent dynamics, and an exosystem whose output is available to onl...
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ISBN:
(纸本)9781467374439
This paper considers the cooperative output regulation problem for linear multi-agent systems with a directed communication graph, heterogeneous linear agent dynamics, and an exosystem whose output is available to only a subset of agents. By using a distributed adaptive observer for the agents to estimate the exogenous signal, a distributed adaptive controller is designed. Compared with the existing works, one main contribution of this paper is that the proposed control schemes can be designed and implemented by each agent in a fully distributed fashion for general directed graphs.
It has been recognized by many researchers that accurate bus travel time prediction is critical for successful deployment of traffic signal priority (TSP) systems. Although there exist a lot of studies on travel time ...
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It has been recognized by many researchers that accurate bus travel time prediction is critical for successful deployment of traffic signal priority (TSP) systems. Although there exist a lot of studies on travel time prediction for Advanced Traveler Information systems (ATIS), this problem for TSP purpose is a little different and the amount of literature is limited. This paper proposes a deep learning based approach for continuous travel time prediction problem. Parameters of the deep network are fine-tuned following a layer-by-layer pre-training procedure on a dataset generated by traffic simulations. Variables that may affect continuous travel time are selected carefully. Experiments are conducted to validate the performance of the proposed model. The results indicate that the proposed model produces prediction with mean absolute error less than 4 seconds, which is accurate enough for TSP operations. This paper also reveals that, except for obvious factors like speed, travel distance and traffic density, the signal time when the prediction is made is also an important factor affecting travel time.
Pose variation is a major challenge in face recognition. In this paper, we propose a novel cross-pose face recognition method by learning associate appearance manifolds to model the connection of faces under different...
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Robust scene-text-extraction system can be used in lots of areas. In this work, we propose to learn co-occurrence of local strokes for robust character recognition by using a spatiality embedded dictionary (SED). Diff...
In the Still-to-Video (S2V) face recognition, each subject is enrolled with only few high resolution images, while the probe is video clips of complex variations. As faces present distinct characteristics under differ...
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Safe moving is a basic ability for a mobile robot, and it is beneficial for the robot to avoid the collisions with the environment if it knows the boundaries between the obstacles and free space. In this paper, a cont...
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With the increasing resolution and availability of digital cameras, text detection in natural scene images receives a growing attention. When taking pictures using a mobile device, people generally only concerned with...
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