Pedestrian Detection Method Based on Roadside Light Detection and Ranging

2021 ◽  
Vol 4 (4) ◽  
Author(s):  
Ziren Gong ◽  
Zhangyu Wang ◽  
Bin Zhou ◽  
Wentao Liu ◽  
Pengfei Liu
Keyword(s):  
Detection Method ◽  
Pedestrian Detection ◽  
Light Detection And Ranging ◽  
Light Detection

scholarly journals A Robust Thermal Infrared Vehicle and Pedestrian Detection Method in Complex Scenes

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1240
Author(s):  
Yang Liu ◽  
Hailong Su ◽  
Cao Zeng ◽  
Xiaoli Li
Keyword(s):  
Detection Method ◽  
Selection Process ◽  
Pedestrian Detection ◽  
Thermal Infrared ◽  
Single Shot ◽  
Detection Algorithms ◽  
Complex Scenes ◽  
Thermal Infrared Images ◽  
Online Feature Selection ◽  
Huge Challenge

In complex scenes, it is a huge challenge to accurately detect motion-blurred, tiny, and dense objects in the thermal infrared images. To solve this problem, robust thermal infrared vehicle and pedestrian detection method is proposed in this paper. An important weight parameter β is first proposed to reconstruct the loss function of the feature selective anchor-free (FSAF) module in its online feature selection process, and the FSAF module is optimized to enhance the detection performance of motion-blurred objects. The proposal of parameter β provides an effective solution to the challenge of motion-blurred object detection. Then, the optimized anchor-free branches of the FSAF module are plugged into the YOLOv3 single-shot detector and work jointly with the anchor-based branches of the YOLOv3 detector in both training and inference, which efficiently improves the detection precision of the detector for tiny and dense objects. Experimental results show that the method proposed is superior to other typical thermal infrared vehicle and pedestrian detection algorithms due to 72.2% mean average precision (mAP).

scholarly journals Using Airborne Light Detection and Ranging (LIDAR) to Characterize Forest Stand Condition on the Kenai Peninsula of Alaska

2009 ◽  
Vol 24 (2) ◽  
pp. 95-102 ◽  
Author(s):  
Hans-Erik Andersen
Keyword(s):  
Forest Inventory ◽  
Laser Scanning ◽  
Three Dimensional ◽  
Grid Cell ◽  
Forest Stand ◽  
Light Detection And Ranging ◽  
Inventory Analysis ◽  
Light Detection ◽  
Individual Tree ◽  
Kenai Peninsula

Abstract Airborne laser scanning (also known as light detection and ranging or LIDAR) data were used to estimate three fundamental forest stand condition classes (forest stand size, land cover type, and canopy closure) at 32 Forest Inventory Analysis (FIA) plots distributed over the Kenai Peninsula of Alaska. Individual tree crown segment attributes (height, area, and species type) were derived from the three-dimensional LIDAR point cloud, LIDAR-based canopy height models, and LIDAR return intensity information. The LIDAR-based crown segment and canopy cover information was then used to estimate condition classes at each 10-m grid cell on a 300 × 300-m area surrounding each FIA plot. A quantitative comparison of the LIDAR- and field-based condition classifications at the subplot centers indicates that LIDAR has potential as a useful sampling tool in an operational forest inventory program.

Precision and shortcomings of yaw error estimation using spinner-based light detection and ranging

Wind Energy ◽  
2012 ◽  
Vol 16 (3) ◽  
pp. 353-366 ◽  
Author(s):  
Knud A. Kragh ◽  
Morten H. Hansen ◽  
Torben Mikkelsen
Keyword(s):  
Error Estimation ◽  
Light Detection And Ranging ◽  
Light Detection

Hybrid Integrated Silicon NitridePolymer Optical Phased Array for Efficient Light Detection and Ranging

2021 ◽  
pp. 1-1
Author(s):  
Chul-Soon Im ◽  
Sung-Moon Kim ◽  
Kyeong-Pyo Lee ◽  
Seong-Hyeon Ju ◽  
Jung-Ho Hong ◽  
...  
Keyword(s):  
Phased Array ◽  
Light Detection And Ranging ◽  
Light Detection ◽  
Optical Phased Array

scholarly journals Random Forest with Adaptive Local Template for Pedestrian Detection

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Tao Xiang ◽  
Tao Li ◽  
Mao Ye ◽  
Zijian Liu
Keyword(s):  
Computer Vision ◽  
Random Forest ◽  
Classification Accuracy ◽  
Template Matching ◽  
Detection Method ◽  
State Of The Art ◽  
Pedestrian Detection ◽  
Sliding Window ◽  
Experimental Results ◽  
Training Samples

Pedestrian detection with large intraclass variations is still a challenging task in computer vision. In this paper, we propose a novel pedestrian detection method based on Random Forest. Firstly, we generate a few local templates with different sizes and different locations in positive exemplars. Then, the Random Forest is built whose splitting functions are optimized by maximizing class purity of matching the local templates to the training samples, respectively. To improve the classification accuracy, we adopt a boosting-like algorithm to update the weights of the training samples in a layer-wise fashion. During detection, the trained Random Forest will vote the category when a sliding window is input. Our contributions are the splitting functions based on local template matching with adaptive size and location and iteratively weight updating method. We evaluate the proposed method on 2 well-known challenging datasets: TUD pedestrians and INRIA pedestrians. The experimental results demonstrate that our method achieves state-of-the-art or competitive performance.

Hardware-in-the-loop projector system for light detection and ranging sensor testing

2012 ◽  
Vol 51 (8) ◽  
pp. 083609-1 ◽  
Author(s):  
Hajin J. Kim ◽  
Charles B. Naumann ◽  
Michael C. Cornell
Keyword(s):  
Light Detection And Ranging ◽  
Hardware In The Loop ◽  
Light Detection

Integrating lidar and geophysical surveys at Falerii Novi and Falerii Veteres (Viterbo)

2009 ◽  
Vol 77 ◽  
pp. 1-27 ◽  
Author(s):  
Rachel Opitz
Keyword(s):  
Sono State ◽  
Light Detection And Ranging ◽  
Light Detection ◽  
Geophysical Surveys

La città romana di Falerii Novi e quella pre-romana di Falerii Veteres vengono riviste in questo articolo attraverso la combinazione di dati da ricognizione lidar (light detection and ranging) e geofisica. La ricognizione lidar fornisce per la prima volta infomiazioni dettagliate sui bordi topograficamente complessi di questi siti e ha permesso di identificare un certo numero di nuove strutture. Osservando tali strutture nel contesto dei dati topografici e geofisici, sono state esplorate le aree urbane periferiche sia come zone per movimento sia come facciate. Tramite questi esempi vengono considerati i potenziali contributi forniti dal lidar alla comprensione generale dell'urbanismo pre-romano e romano.

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