Wavelet Transform-Based High-Definition Map Construction From a Panoramic Camera

2021 ◽  
Vol 26 (5) ◽  
pp. 569-576
Author(s):  
Hanyang Zhuang ◽  
Xuejun Zhou ◽  
Chunxiang Wang ◽  
Yuhan Qian
Author(s):  
Shichang Du ◽  
Changping Liu ◽  
Lifeng Xi

The surface appearance is sensitive to change in the manufacturing process and is one of the most important product quality characteristics. The classification of workpiece surface patterns is critical for quality control, because it can provide feedback on the manufacturing process. In this study, a novel classification approach for engineering surfaces is proposed by combining dual-tree complex wavelet transform (DT-CWT) and selective ensemble classifiers called modified matching pursuit optimization with multiclass support vector machines ensemble (MPO-SVME), which adopts support vector machine (SVM) as basic classifiers. The dual-tree wavelet transform is used to decompose three-dimensional (3D) workpiece surfaces, and the features of workpiece surface are extracted from wavelet sub-bands of each level. Then MPO-SVME is developed to classify different workpiece surfaces based on the extracted features and the performance of the proposed approach is evaluated by computing its classification accuracy. The performance of MPO-SVME is validated in case study, and the results demonstrate that MPO-SVME can increase the classification accuracy with only a handful of selected classifiers.


Author(s):  
Tae Seok Choi ◽  
Ha Su Yoon ◽  
Yun Soo Choi ◽  
Won Jong Lee ◽  
Soo Young Chang

2020 ◽  
Vol 32 (3) ◽  
pp. 613-623
Author(s):  
Kenta Maeda ◽  
Junya Takahashi ◽  
Pongsathorn Raksincharoensak ◽  
◽  

This report describes a map construction and evaluation method based on lane-marker information for autonomous driving. Autonomous driving systems typically require digital high-definition (HD) maps to correct the current position of autonomous vehicles by using localization techniques. However, an HD map is usually costly to generate because it requires a special-purpose vehicle and mapping system with precise and expensive sensors. This report presents a map construction method that uses cost-efficient on-board cameras. We implement two types of map construction methods with two different cameras in terms of range and field of view and test their performances to determine the minimum sensor specification required for autonomous driving. This report also presents a constructed map evaluation method to determine the “usability” of the map for autonomous driving. Given that the system cannot obtain “true” positions of landmarks, the method judges whether the constructed map contains sufficient information for localization via the presented indices “lateral-distance error.” The methods are verified based on mapping and localization errors determined via manual driving tests. Furthermore, the smoothness of steering maneuvers is determined by conducting autonomous driving tests on a proving ground. The results reveal the necessary conditions of sensor requirements, i.e., the constant visibility of landmarks is one of the key factors for ego-localization to conduct autonomous driving.


Author(s):  
E. Wisse ◽  
A. Geerts ◽  
R.B. De Zanger

The slowscan and TV signal of the Philips SEM 505 and the signal of a TV camera attached to a Leitz fluorescent microscope, were digitized by the data acquisition processor of a Masscomp 5520S computer, which is based on a 16.7 MHz 68020 CPU with 10 Mb RAM memory, a graphics processor with two frame buffers for images with 8 bit / 256 grey values, a high definition (HD) monitor (910 × 1150), two hard disks (70 and 663 Mb) and a 60 Mb tape drive. The system is equipped with Imaging Technology video digitizing boards: analog I/O, an ALU, and two memory mapped frame buffers for TV images of the IP 512 series. The Masscomp computer has an ethernet connection to other computers, such as a Vax PDP 11/785, and a Sun 368i with a 327 Mb hard disk and a SCSI interface to an Exabyte 2.3 Gb helical scan tape drive. The operating system for these computers is based on different versions of Unix, such as RTU 4.1 (including NFS) on the acquisition computer, bsd 4.3 for the Vax, and Sun OS 4.0.1 for the Sun (with NFS).


2019 ◽  
Vol 4 (2) ◽  
pp. 356-362
Author(s):  
Jennifer W. Means ◽  
Casey McCaffrey

Purpose The use of real-time recording technology for clinical instruction allows student clinicians to more easily collect data, self-reflect, and move toward independence as supervisors continue to provide continuation of supportive methods. This article discusses how the use of high-definition real-time recording, Bluetooth technology, and embedded annotation may enhance the supervisory process. It also reports results of graduate students' perception of the benefits and satisfaction with the types of technology used. Method Survey data were collected from graduate students about their use and perceived benefits of advanced technology to support supervision during their 1st clinical experience. Results Survey results indicate that students found the use of their video recordings useful for self-evaluation, data collection, and therapy preparation. The students also perceived an increase in self-confidence through the use of the Bluetooth headsets as their supervisors could provide guidance and encouragement without interrupting the flow of their therapy sessions by entering the room to redirect them. Conclusions The use of video recording technology can provide opportunities for students to review: videos of prospective clients they will be treating, their treatment videos for self-assessment purposes, and for additional data collection. Bluetooth technology provides immediate communication between the clinical educator and the student. Students reported that the result of that communication can improve their self-confidence, perceived performance, and subsequent shift toward independence.


PsycCRITIQUES ◽  
2004 ◽  
Vol 49 (Supplement 4) ◽  
Author(s):  
Stephen F. Davis
Keyword(s):  

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