scholarly journals Efficient Vehicle Detection and Distance Estimation Based on Aggregated Channel Features and Inverse Perspective Mapping from a Single Camera

Symmetry ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 1205
Author(s):  
Jong Bae Kim
Keyword(s):  
Real Time ◽  
Autonomous Vehicles ◽  
Distance Estimation ◽  
Vehicle Detection ◽  
Input Image ◽  
Three Dimensions ◽  
Real Time Processing ◽  
Time Processing ◽  
Histograms Of Oriented Gradients ◽  
Inverse Perspective Mapping

In this paper a method for detecting and estimating the distance of a vehicle driving in front using a single black-box camera installed in a vehicle was proposed. In order to apply the proposed method to autonomous vehicles, it was required to reduce the throughput and speed-up the processing. To do this, the proposed method decomposed the input image into multiple-resolution images for real-time processing and then extracted the aggregated channel features (ACFs). The idea was to extract only the most important features from images at different resolutions symmetrically. A method of detecting an object and a method of estimating a vehicle’s distance from a bird’s eye view through inverse perspective mapping (IPM) were applied. In the proposed method, ACFs were used to generate the AdaBoost-based vehicle detector. The ACFs were extracted from the LUV color, edge gradient, and orientation (histograms of oriented gradients) of the input image. Subsequently, by applying IPM and transforming a 2D input image into 3D by generating an image projected in three dimensions, the distance between the detected vehicle and the autonomous vehicle was detected. The proposed method was applied in a real-world road environment and showed accurate results for vehicle detection and distance estimation in real-time processing. Thus, it was showed that our method is applicable to autonomous vehicles.

scholarly journals Automatic Vehicle License Plate Extraction Using Region-Based Convolutional Neural Networks and Morphological Operations

Symmetry ◽  
2019 ◽  
Vol 11 (7) ◽  
pp. 882 ◽  
Author(s):  
JongBae Kim
Keyword(s):  
Real Time ◽  
Detection Rate ◽  
Input Image ◽  
License Plate ◽  
Morphological Operations ◽  
Morphological Operation ◽  
Edge Pixel ◽  
Real Time Processing ◽  
Time Processing ◽  
Candidate Regions

The number and range of the candidate vehicle license plate (VLP) region affects the result of the VLP extraction symmetrically. Therefore, in order to improve the VLP extraction rate, many candidate VLP regions are selected. However, there is a problem that the processing time increases symmetrically. In this paper, we propose a method that allows detecting a vehicle license plate in the real-time mode. To do this, the proposed method makes use of the region-based convolutional neural network (R-CNN) method and morphological operations. The R-CNN method is a deep learning method that selects a large number of candidate regions from an input image and compares them to determine whether objects of interest are included. However, this method has limitations when used in real-time processing. Therefore, to address this limitation in the proposed method, while selecting a candidate vehicle region, the selection range is reduced based on the size and position of the vehicle in the input image; hence, processing can be performed quickly. A vehicle license plate is detected by performing a morphological operation based on the edge pixel distribution of the detected vehicle region. Experimental results show that the detection rate of vehicles is approximately 92% in real road environments, and the detection rate of vehicle license plates is approximately 83%.

GPU Acceleration of Algorithm to Design Directional Volumetric Display for Real-time Processing

2019 ◽  
pp. 989
Author(s):  
Daiki Matsumoto ◽  
Ryuji Hirayama ◽  
Naoto Hoshikawa ◽  
Hirotaka Nakayama ◽  
Tomoyoshi Shimobaba ◽  
...  
Keyword(s):  
Real Time ◽  
Gpu Acceleration ◽  
Real Time Processing ◽  
Time Processing ◽  
Volumetric Display

Putting up barriers

2017 ◽  
Author(s):  
David J. Lobina
Keyword(s):  
Knowledge Base ◽  
Real Time ◽  
Language Processing ◽  
Cognitive Domain ◽  
Linguistic Knowledge ◽  
Levels Of Explanation ◽  
Real Time Processing ◽  
Time Processing ◽  
Neural Underpinnings ◽  
Different Levels

The study of cognitive phenomena is best approached in an orderly manner. It must begin with an analysis of the function in intension at the heart of any cognitive domain (its knowledge base), then proceed to the manner in which such knowledge is put into use in real-time processing, concluding with a domain’s neural underpinnings, its development in ontogeny, etc. Such an approach to the study of cognition involves the adoption of different levels of explanation/description, as prescribed by David Marr and many others, each level requiring its own methodology and supplying its own data to be accounted for. The study of recursion in cognition is badly in need of a systematic and well-ordered approach, and this chapter lays out the blueprint to be followed in the book by focusing on a strict separation between how this notion applies in linguistic knowledge and how it manifests itself in language processing.

scholarly journals Limits on expectation-based processing: Use of grammatical aspect for co-reference in L2

2020 ◽  
pp. 1-25
Author(s):  
Theres Grüter ◽  
Hannah Rohde
Keyword(s):  
Real Time ◽  
Language Processing ◽  
Judgment Task ◽  
Linguistic Knowledge ◽  
Real Time Processing ◽  
Time Processing ◽  
Grammatical Aspect ◽  
Level Information ◽  
Native Speakers Of English ◽  
Reference Processing

Abstract This study examines the use of discourse-level information to create expectations about reference in real-time processing, testing whether patterns previously observed among native speakers of English generalize to nonnative speakers. Findings from a visual-world eye-tracking experiment show that native (L1; N = 53) but not nonnative (L2; N = 52) listeners’ proactive coreference expectations are modulated by grammatical aspect in transfer-of-possession events. Results from an offline judgment task show these L2 participants did not differ from L1 speakers in their interpretation of aspect marking on transfer-of-possession predicates in English, indicating it is not lack of linguistic knowledge but utilization of this knowledge in real-time processing that distinguishes the groups. English proficiency, although varying substantially within the L2 group, did not modulate L2 listeners’ use of grammatical aspect for reference processing. These findings contribute to the broader endeavor of delineating the role of prediction in human language processing in general, and in the processing of discourse-level information among L2 users in particular.

scholarly journals A Real Time Processing system for big data in astronomy: Applications to HERA

2021 ◽  
pp. 100489
Author(s):  
Paul La Plante ◽  
P.K.G. Williams ◽  
M. Kolopanis ◽  
J.S. Dillon ◽  
A.P. Beardsley ◽  
...  
Keyword(s):  
Big Data ◽  
Real Time ◽  
Processing System ◽  
Real Time Processing ◽  
Time Processing

Real-Time Processing of Spaceborne SAR Data With Nonlinear Trajectory Based on Variable PRF

2021 ◽  
pp. 1-12
Author(s):  
Jianlai Chen ◽  
Junchao Zhang ◽  
Yanghao Jin ◽  
Hanwen Yu ◽  
Buge Liang ◽  
...  
Keyword(s):  
Real Time ◽  
Real Time Processing ◽  
Time Processing ◽  
Sar Data

scholarly journals A Set of Integral Grid-Coding Algebraic Operations Based on GeoSOT-3D

2021 ◽  
Vol 10 (7) ◽  
pp. 489
Author(s):  
Kaihua Hou ◽  
Chengqi Cheng ◽  
Bo Chen ◽  
Chi Zhang ◽  
Liesong He ◽  
...  
Keyword(s):  
Real Time ◽  
Spatial Information ◽  
Data Retrieval ◽  
Geospatial Data ◽  
Algebraic Operation ◽  
Real Time Processing ◽  
C Language ◽  
Time Processing ◽  
Binary Operations ◽  
Set Operations

As the amount of collected spatial information (2D/3D) increases, the real-time processing of these massive data is among the urgent issues that need to be dealt with. Discretizing the physical earth into a digital gridded earth and assigning an integral computable code to each grid has become an effective way to accelerate real-time processing. Researchers have proposed optimization algorithms for spatial calculations in specific scenarios. However, a complete set of algorithms for real-time processing using grid coding is still lacking. To address this issue, a carefully designed, integral grid-coding algebraic operation framework for GeoSOT-3D (a multilayer latitude and longitude grid model) is proposed. By converting traditional floating-point calculations based on latitude and longitude into binary operations, the complexity of the algorithm is greatly reduced. We then present the detailed algorithms that were designed, including basic operations, vector operations, code conversion operations, spatial operations, metric operations, topological relation operations, and set operations. To verify the feasibility and efficiency of the above algorithms, we developed an experimental platform using C++ language (including major algorithms, and more algorithms may be expanded in the future). Then, we generated random data and conducted experiments. The experimental results show that the computing framework is feasible and can significantly improve the efficiency of spatial processing. The algebraic operation framework is expected to support large geospatial data retrieval and analysis, and experience a revival, on top of parallel and distributed computing, in an era of large geospatial data.

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