A Fast Stereo Matching Algorithm Based on Fixed-Window

2013 ◽  
Vol 411-414 ◽  
pp. 1305-1313 ◽  
Author(s):  
Guan Wen Zheng ◽  
Xiu Hua Jiang
Keyword(s):  
Real Time ◽  
Stereo Matching ◽  
Computational Cost ◽  
Experimental Results ◽  
Matching Algorithm ◽  
Real Time Applications ◽  
Stereo Algorithm ◽  
Repetitive Pattern

This paper presents a fast local stereo algorithm that suitable to real time applications. Thanks to the techniques like Box-filtering, fixed-window-based stereo matching algorithms can be really fast, but perform not well in some areas, i.e. the repetitive pattern and low texture areas. In order to improve the reliability of fixed-window algorithm and keep the algorithms speed, the proposed approach can deal with the repetitive pattern and low texture areas at a small computational cost. Experimental results show that the proposed approach provides a big improvement in accuracy compare to fixed-window algorithm, and the speed of the algorithm is still fast.

scholarly journals OFCOD: On the Fly Clustering Based Outlier Detection Framework

Data ◽  
2020 ◽  
Vol 6 (1) ◽  
pp. 1
Author(s):  
Ahmed Elmogy ◽  
Hamada Rizk ◽  
Amany M. Sarhan
Keyword(s):  
Data Mining ◽  
Image Processing ◽  
Intrusion Detection ◽  
Real Time ◽  
Outlier Detection ◽  
Real World ◽  
Medical Data ◽  
Experimental Results ◽  
Real Time Applications ◽  
Real World Datasets

In data mining, outlier detection is a major challenge as it has an important role in many applications such as medical data, image processing, fraud detection, intrusion detection, and so forth. An extensive variety of clustering based approaches have been developed to detect outliers. However they are by nature time consuming which restrict their utilization with real-time applications. Furthermore, outlier detection requests are handled one at a time, which means that each request is initiated individually with a particular set of parameters. In this paper, the first clustering based outlier detection framework, (On the Fly Clustering Based Outlier Detection (OFCOD)) is presented. OFCOD enables analysts to effectively find out outliers on time with request even within huge datasets. The proposed framework has been tested and evaluated using two real world datasets with different features and applications; one with 699 records, and another with five millions records. The experimental results show that the performance of the proposed framework outperforms other existing approaches while considering several evaluation metrics.

scholarly journals Real-Time Vehicle Make and Model Recognition with the Residual SqueezeNet Architecture

Sensors ◽  
2019 ◽  
Vol 19 (5) ◽  
pp. 982 ◽  
Author(s):  
Hyo Lee ◽  
Ihsan Ullah ◽  
Weiguo Wan ◽  
Yongbin Gao ◽  
Zhijun Fang
Keyword(s):  
Deep Learning ◽  
Real Time ◽  
Large Scale ◽  
Recognition Rate ◽  
Experimental Results ◽  
Learning Approach ◽  
Deep Model ◽  
Proposed Model ◽  
Real Time Applications ◽  
Model Recognition

Make and model recognition (MMR) of vehicles plays an important role in automatic vision-based systems. This paper proposes a novel deep learning approach for MMR using the SqueezeNet architecture. The frontal views of vehicle images are first extracted and fed into a deep network for training and testing. The SqueezeNet architecture with bypass connections between the Fire modules, a variant of the vanilla SqueezeNet, is employed for this study, which makes our MMR system more efficient. The experimental results on our collected large-scale vehicle datasets indicate that the proposed model achieves 96.3% recognition rate at the rank-1 level with an economical time slice of 108.8 ms. For inference tasks, the deployed deep model requires less than 5 MB of space and thus has a great viability in real-time applications.

scholarly journals A Real-Time Range Finding System with Binocular Stereo Vision

10.5772/50921 ◽  
2012 ◽  
Vol 9 (1) ◽  
pp. 26 ◽  
Author(s):  
Xiao-Bo Lai ◽  
Hai-Shun Wang ◽  
Yue-Hong Xu
Keyword(s):  
Real Time ◽  
Stereo Vision ◽  
Stereo Matching ◽  
Single Point ◽  
Time Range ◽  
Real Time Control ◽  
Matching Algorithm ◽  
Range Finding ◽  
Binocular Stereo Vision ◽  
Binocular Stereo

To acquire range information for mobile robots, a TMS320DM642 DSP-based range finding system with binocular stereo vision is proposed. Firstly, paired images of the target are captured and a Gaussian filter, as well as improved Sobel kernels, are achieved. Secondly, a feature-based local stereo matching algorithm is performed so that the space location of the target can be determined. Finally, in order to improve the reliability and robustness of the stereo matching algorithm under complex conditions, the confidence filter and the left-right consistency filter are investigated to eliminate the mismatching points. In addition, the range finding algorithm is implemented in the DSP/BIOS operating system to gain real-time control. Experimental results show that the average accuracy of range finding is more than 99% for measuring single-point distances equal to 120cm in the simple scenario and the algorithm takes about 39ms for ranging a time in a complex scenario. The effectivity, as well as the feasibility, of the proposed range finding system are verified.

scholarly journals A CONTRAST-BASED APPROACH TO THE IDENTIFICATION OF TEXTURE FAULTS

2002 ◽  
Vol 16 (02) ◽  
pp. 193-214
Author(s):  
FRANCESCO G. B. DE NATALE ◽  
FABRIZIO GRANELLI ◽  
GIANNI VERNAZZA
Keyword(s):  
Computational Complexity ◽  
Real Time ◽  
Texture Analysis ◽  
Visual Inspection ◽  
Experimental Results ◽  
Discrimination Capability ◽  
The Past ◽  
Inspection Systems ◽  
Real Time Applications ◽  
Good Attitude

Texture analysis based on the extraction of contrast features is very effective in terms of both computational complexity and discrimination capability. In this framework, max–min approaches have been proposed in the past as a simple and powerful tool to characterize a statistical texture. In the present work, a method is proposed that allows exploiting the potential of max–min approaches to efficiently solve the problem of detecting local alterations in a uniform statistical texture. Experimental results show a high defect discrimination capability, and a good attitude to real-time applications, which make it particularly attractive for the development of industrial visual inspection systems.

Real time area-based stereo matching algorithm for multimedia video devices

2013 ◽  
Vol 21 (4) ◽  
Author(s):  
T. Hachaj ◽  
M. Ogiela
Keyword(s):  
Real Time ◽  
Stereo Matching ◽  
Global Memory ◽  
Stereo Pair ◽  
Processing Unit ◽  
Process Data ◽  
Matching Algorithm ◽  
Knowing That ◽  
Algorithm Configuration ◽  
Graphical Processing

AbstractIn this paper we investigate stereovision algorithms that are suitable for multimedia video devices. The main novel contribution of this article is detailed analysis of modern graphical processing unit (GPU)-based dense local stereovision matching algorithm for real time multimedia applications. We considered two GPU-based implementations and one CPU implementation (as the baseline). The results (in terms of frame per second, fps) were measured twenty times per algorithm configuration and, then averaged (the standard deviation was below 5%). The disparity range was [0,20], [0,40], [0,60], [0,80], [0,100] and [0,120]. We also have used three different matching window sizes (3×3, 5×5 and 7×7) and three stereo pair image resolutions 320×240, 640×480 and 1024×768. We developed our algorithm under assumption that it should process data with the same speed as it arrives from captures’ devices. Because most popular of the shelf video cameras (multimedia video devices) capture data with the frequency of 30Hz, this frequency was threshold to consider implementation of our algorithm to be “real time”. We have proved that our GPU algorithm that uses only global memory can be used successfully in that kind of tasks. It is very important because that kind of implementation is more hardware-independent than algorithms that operate on shared memory. Knowing that we might avoid the algorithms failure while moving the multimedia application between machines operating different hardware. From our knowledge this type of research has not been yet reported.

Research on Stereo Matching Algorithm in Intelligent Vehicle Application

2014 ◽  
Vol 678 ◽  
pp. 35-38 ◽  
Author(s):  
Peng He ◽  
Feng Gao
Keyword(s):  
Stereo Vision ◽  
Stereo Matching ◽  
Driver Assistance System ◽  
Experimental Results ◽  
Assistance System ◽  
Intelligent Vehicle ◽  
Driver Assistance ◽  
Matching Algorithm ◽  
Environment Perception ◽  
Vehicle Technologies

Perception of environment in front of driving vehicle is a core investigation theme of intelligent vehicle technologies aiming to increase safety, convenience and efficiency of driving. Using stereo vision for environment perception is a hot technology. This paper developed an algorithm for stereo matching in intelligent vehicle application. The experimental results indicate that this algorithm is effective. Furthermore, this algorithm paves the way for the implementation of automotive driver assistance system.

scholarly journals Real‐time multi‐window stereo matching algorithm with fuzzy logic

2021 ◽  
Vol 15 (3) ◽  
pp. 208-223
Author(s):  
Héctor‐Daniel Vázquez‐Delgado ◽  
Madaín Pérez‐Patricio ◽  
Abiel Aguilar‐González ◽  
Miguel‐Octavio Arias‐Estrada ◽  
Marco‐Antonio Palacios‐Ramos ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Real Time ◽  
Stereo Matching ◽  
Matching Algorithm

Aligning Genomic Sequence Applied in Stereo Matching

2011 ◽  
Vol 121-126 ◽  
pp. 4357-4361
Author(s):  
Shu Chun Yu ◽  
Xiao Yang Yu ◽  
Jian Ying Fan ◽  
Hai Bin Wu
Keyword(s):  
Stereo Matching ◽  
Genomic Sequence ◽  
Experimental Results ◽  
Genomic Sequences ◽  
Control Points ◽  
Matching Method ◽  
Matching Algorithm ◽  
Fast Speed

The stereo matching algorithm based on aligning genomic sequence is proposed in the paper. This method is divided in three steps: do genomic sequence on the same name epipolar of stereo matching, get branch matrix by establishing genomic sequences using the same name epipolar after being genomic sequences, control points technology and dynamic backdate method to get disparity. The experimental results show that stereo matching method based on genomic sequences has fast speed and good matching quality.

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