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A Robust and Real-Time RGB-D SLAM Method with Dynamic Point recognition and Depth Segmentation Optimization 7th

A Robust and Real-Time RGB-D SLAM Method with Dynamic Point ...

引用

7th Chinese conference on pattern recognition and Computer Vision

作者： Chen, Shuaixin Gan, Baolin Zhang, Congxuan Chen, Zhen Lu, Ke Lu, Feng Nanchang Hangkong Univ Nanchang 330063 Jiangxi Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China

ISBN: (纸本)9789819786916;9789819786923

Simultaneous localization and mapping (SLAM), as one of the core prerequisite technologies for intelligent mobile robots, has attracted much attention in recent years. However, the applicability of SLAM algorithms in practical scenarios is limited due to the strict assumptions of static environments. Although many recent SLAM systems have been devoted to introducing semantic segmentation or object detection schemes to identify dynamic regions, these methods fail to detect regions with unknown semantics and are highly time-consuming. To address the abovementioned problems, we propose a robust and real-time RGB-D SLAM method with dynamic point recognition and depth segmentation optimization. Specifically, we first plan a self-adaptive feature point tracking scheme based on sparse optical flows, which accelerates the feature point tracking process and avoids local optima. Then, we design a dynamic feature point recognition model that uses motion information and spatial distribution patterns to distinguish between dynamic and static point clusters. Finally, we exploit a depth segmentation optimization scheme to recover the misclassified feature points, which further improves the SLAM performance of the model. The experimental results obtained from a comparison between our method and several state-of-the-art (SOTA) models demonstrate that the proposed method achieves the best performance among the geometry-based methods and performs competitively relative to the deep learning-based models, especially in highly dynamic environments.

关键词： SLAM dynamic environments optical flow spatial distribution pattern depth segmentation

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optical spatial filtering for image encryption and security systems 9

Optical spatial filtering for image encryption and security ...

引用

conference on optical pattern recognition ix

作者： Javidi, B Univ Connecticut Dept Elect Engn Storrs CT 06269 USA

This paper reviews a number of optical information processing techniques for encryption, security and anticounterfeiting.

ISBN: (纸本)0819428353

This paper reviews a number of optical information processing techniques for encryption, security and anticounterfeiting.

关键词： optical pattern recognition encryption security anticounterfeiting optical information processing

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Hybrid real-time optical correlator 9

Hybrid real-time optical correlator

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conference on optical pattern recognition ix

作者： Qin, WF Wang, RL Chen, GF Yan, YX Chinese Acad Sci Shanghai Inst Tech Phys Optoelect Engn Res Ctr Shanghai 200083 Peoples R China

ISBN: (纸本)0819428353

A new type of information processing system is developed. The processing is implemented by using hybrid architecture of Vander-Lugt optical correlator and joint transform correlator. Zn one optical setup, joint transform correlator is used for object tracking and Vander-Lugt optical correlator is used for object recognition respectively. The experiments show that we can get good results.

关键词： optical correlator object tracking pattern recognition

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Feature enhancement and similarity suppression algorithm for noisy pattern recognition 9

Feature enhancement and similarity suppression algorithm for...

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conference on optical pattern recognition ix

作者： Stamos, E Selviah, DR Univ London Univ Coll Dept Elect & Elect Engn London WC1E 7JE England

ISBN: (纸本)0819428353

A novel feature enhancement and similarity suppression algorithm is presented. This algorithm can be used for training matched filter based optical pattern recognition systems or for the correct recovery of noisy images from optical memories such as optical disks. The underlying theory and the results from computer simulations using human faces are presented. Some preliminary results have shown high probability of recognition in pattern recognition tests using the training data.

关键词： optical pattern recognition feature extraction optical correlators training algorithms template or spatial filter design

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Image defocusing in Nature and technique in recognition process 9

Image defocusing in Nature and technique in recognition proc...

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conference on optical pattern recognition ix

作者： Ginzburg, V Consultant (United States)

ISBN: (纸本)0819428353

Application of visual image defocusing is illustrated as a technique for generalization, recognition and control. Specifically, formation of generalized images of objects by using a set of elementary patterns is described. This "geometric alphabet".is created by two basic figures: a stripe and sound spot. It is known from physiology that these figures produce response in special cells of the visual cortex of living organisms. Boolean algebra (Venn's diagrams) is used to obtain "letters" and generalized images ("geometrical words") by computer simulation. The results of physical and computer experiments are given. A diagram of an anthropomorphic robot is presented together with model experiments on "drawing" generalized images.

关键词： optical pattern recognition defocusing visual system informative fragments image perception anthropomorphic robot

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Rotation-invariant projection-slice filter 9

Rotation-invariant projection-slice filter

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conference on optical pattern recognition ix

作者： Riasati, VR Banerjee, PP Abushagur, MAG Gregory, DA Univ Alabama Huntsville AL 35899 USA

ISBN: (纸本)0819428353

In this paper the projection-slice SDF (PSDF) filter for rotation invariant response is discussed for pattern recognition applications. This method uses one half of a slice of the Fourier transform of the object to generate the transfer function of the filter. This is accomplished by repeating the half slice in the Fourier domain through 2 pi radians about the zero-frequency point of the Fourier plane. This filter has the advantage of always matching at least one half of a slice of the Fourier transform of any rotation of the image. An analytical discussion of the filter transfer function and impulse response are presented along with simulated correlation results for a particular target scene including decoys. These results are evaluated using the peak correlation value, peak correlation energy, and the Fisher metric for performance.

关键词： synthetic discriminant functions SDF ring filter projection-slice theorem PSDF optical pattern recognition

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Use of laser radar imagery in optical pattern recognition: the optical processor enhanced ladar (OPEL) program 9

Use of laser radar imagery in optical pattern recognition: t...

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conference on optical pattern recognition ix

作者： Goldstein, DH Mills, SA Dydyk, RB USAF Res Lab Munit Directorate Eglin AFB FL 32542 USA

ISBN: (纸本)0819428353

The optical Processor Enhanced Ladar (OPEL) program is designed to evaluate the capabilities of a seeker obtained by integrating two state-of-the-art technologies, laser radar, or ladar, and optical correlation. The program is a thirty-two month effort to build, optimize, and test a breadboard seeker system (the OPEL System) that incorporates these two promising technologies. Laser radars produce both range and intensity image information. Use of this information in an optical correlator is described. A correlator with binary phase input and ternary amplitude and phase filter capability is assumed. Laser radar imagery was collected on five targets over 360 degrees of azimuth from 3 elevation angles. This imagery was then processed to provide training sets in preparation for filter construction. This paper reviews the ladar and optical correlator technologies used, outlines the OPEL program, and describes the OPEL system.

关键词： laser radar ladar optical correlation optical processing optical pattern recognition seeker

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A novel, fast-learning, noniterative neural network in pattern-recognition

A novel, fast-learning, noniterative neural network in patte...

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conference on Machine Vision Applications in Industrial Inspection ix

作者： Hu, CLJ So Illinois Univ Dept Elect Engn Carbondale IL 62901 USA

ISBN: (纸本)0819439797

When the analog-to-digital mapping to be learned by any pattern recognition scheme satisfies a certain PLI condition, a one-layered, hard-limited perceptron (OHP) is enough to be used for recognizing any unlearned patterns with high robustness. Generally, the PLI condition is satisfied for most practical pattern recognition applications. When this condition is satisfied, then an automatic feature extraction scheme can he derived from an N-dimension geometry point of view. This automatic scheme will automatically extract the most distinguished parts of the pattern Vectors used in the training. It selects the feature vectors (sub-vectors of the pattern vectors) automatically according to the descending order of the volumes of the parallelepiped spanned by these sub-vectors. Theoretical derivation revealing the physical nature of this process and its effect in optimizing the robustness of this novel pattern recognition system will be reported in detail.

关键词： pattern recognition automatic feature extraction

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optical morphological SDF filter for multiple-object recognition 9

Optical morphological SDF filter for multiple-object recogni...

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conference on optical pattern recognition ix

作者： Kim, JC Kim, JW Lee, HW Doh, YH Kim, SJ Kyungpook Jr Coll Dept Elect Engn Kyungpook 750050 South Korea

ISBN: (纸本)0819428353

A new nonlinear morphological detection algorithm is proposed for input scenes with a number of objects present in a clutter. It uses a synthetic discriminant function(SDF) to form the matched spatial filter(MSF) of the structuring element(SE) used in the hit-miss transform(HMT) detection. The SDF synthetic technique is used to adapt intraclass distortions and interclass similarity, where an HMT is used to adapt noisy and cluttered scenes. Simulation results show the proposed algorithm is an attractive nonlinear optical image processing technique that can be applied to an HMT detection to improve both the false alarm rate and its ability to detect multiple-object with distortions and clutter.

关键词： hit-miss transform multiple-object recognition synthetic discriminant function filter

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Feature competition and feature extraction in a noniterative neural network pattern recognition scheme 9

Feature competition and feature extraction in a noniterative...

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conference on optical pattern recognition ix

作者： Hu, CLJ So Illinois Univ Dept Elect Engn Carbondale IL 62901 USA

ISBN: (纸本)0819428353

As we published in the last few years [1-7], when the given input-output training vector pairs satisfy a PLI (positive-linear-independency) condition, the training and the application of a hard-limited neural network can be achieved non-iteratively with very short training time and very robust recognition when it is applied to recognize any untrained patterns. The key feature in this novel pattern recognition system is the use of slack constants in solving the connection matrix when the PLI condition is satisfied. Generally there are infinitely many ways of selecting the slack constants for meeting the training-recognition goal but there is only one way to select them if an optimal robustness is sought in the recognition of the untrained patterns. This particular way of selecting the slack constants carries some special physical properties of the system - the automatic future extraction in the learning mode and the automatic feature competition in the recognition mode. Physical significance as well as mathematical analysis of these novel properties are to be explained in detail in this article. Real-time experiments are to be presented in an unedited movie. It is seen that in the system, the training of 4 hand-written characters is close to real time (<0.1 sec.) and the recognition of the untrained hand-written characters is >90% accurate.

关键词： pattern recognition image processing novel neural network

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