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False Positive Removal for 3D Vehicle Detection with Penetrated Point Classifier [article]

Sungmin Woo, Sangwon Hwang, Woojin Kim, Junhyeop Lee, Dogyoon Lee, Sangyoun Lee
2020 arXiv   pre-print
Recently, researchers have been leveraging LiDAR point cloud for higher accuracy in 3D vehicle detection.  ...  This vulnerability leads to numerous false positive boxes at high recall positions, where objects are occasionally predicted with few points.  ...  In this paper, we propose a new approach in 3D vehicle detection for the false positive removal task.  ... 
arXiv:2005.13153v2 fatcat:bsngeqwomndhnmvvns2yagwasu

A Cooperative Perception Environment for Traffic Operations and Control [article]

Hanlin Chen, Brian Liu, Xumiao Zhang, Feng Qian, Z. Morley Mao, Yiheng Feng
2022 arXiv   pre-print
The state-of-the-art 3D detection models are applied to detect vehicles in the merged point cloud.  ...  Results show that very low penetration rates of CAV plus an infrastructure sensor are sufficient to achieve comparable performance with 30% or higher penetration rates of connected vehicles (CV).  ...  Zhitong Huang from Leidos and the CARMA Program at FHWA for their technical support in the co-simulation environment. The views presented in this paper are those of the authors alone.  ... 
arXiv:2208.02792v1 fatcat:cy3fawaxanconjnt3n7uaaa67i

3D object detection from roadside data using laser scanners

Jimmy Tang, Avideh Zakhor, J. Angelo Beraldin, Geraldine S. Cheok, Michael B. McCarthy, Ulrich Neuschaefer-Rube, Atilla M. Baskurt, Ian E. McDowall, Margaret Dolinsky
2011 Three-Dimensional Imaging, Interaction, and Measurement  
We show that our proposed method is effective in identifying objects for several road datasets collected with various object locations and vehicle speeds.  ...  In this thesis, we develop a method to detect objects of a specific size lying on a road using an acquisition vehicle equipped with forward looking Light Detection And Range (LiDAR) sensors and inertial  ...  An example of a missed detection of an object is shown in Figure 17: (a) Point cloud (b) 3D mesh of a missed detection.An example of a false alarm is shown inFigure 18: Two examples of falsely detected  ... 
doi:10.1117/12.872620 dblp:conf/3dica/TangZ11 fatcat:usul35rfq5bvrdwebfok6isdpq

Pedestrian detection for underground mine vehicles using thermal images

J. S. Dickens, M. A. van Wyk, J. J. Green
2011 IEEE Africon '11  
The proposed collision detection system uses the fusion of a three-dimensional (3D) sensor and thermal infrared camera for human detection and tracking.  ...  Mine vehicles are a leading cause of mining fatalities. A reliable anti-collision system is needed to prevent vehicle-personnel collisions.  ...  The main difference between the two is that the Parzen classifier achieves a maximum true positive rate of 98% while the neural network can detect 100% of the targets (albeit with a high false positive  ... 
doi:10.1109/afrcon.2011.6072167 fatcat:jtiw5cycjrcjzehg52cvjit7ke

Ambient awareness for agricultural robotic vehicles

Giulio Reina, Annalisa Milella, Raphaël Rouveure, Michael Nielsen, Rainer Worst, Morten R. Blas
2016 Biosystems Engineering  
Novel methods for their combination are proposed to automatically detect obstacles and discern traversable from non-traversable areas.  ...  Accurate and robust environmental perception is a critical requirement to address unsolved issues including safe interaction with field workers and animals, obstacle detection in controlled traffic applications  ...  ACKNOWLEDGMENT The financial support of the FP7 ERA-NET ICT-AGRI through the grants Ambient Awareness for Autonomous Agricultural Vehicles (QUAD-AV) and Simultaneous Safety and Surveying for Collaborative  ... 
doi:10.1016/j.biosystemseng.2015.12.010 fatcat:25msz6wxhrfllpsiljprn6adlq

Distributed Road Surface Condition Monitoring Using Mobile Phones [chapter]

Mikko Perttunen, Oleksiy Mazhelis, Fengyu Cong, Mikko Kauppila, Teemu Leppänen, Jouni Kantola, Jussi Collin, Susanna Pirttikangas, Janne Haverinen, Tapani Ristaniemi, Jukka Riekki
2011 Lecture Notes in Computer Science  
approach for feature extraction and demonstrating its positive effect in multiple feature sets for the road surface anomaly detection task. 4) A framework for visually analyzing the classifier predictions  ...  The problem we consider is to detect road surface anomalies that, when left unreported, can cause wear of vehicles, lesser driving comfort and vehicle controllability, or an accident.  ...  This work was supported by TEKES as part of the Cooperative Traffic ICT program of TIVIT (Finnish Strategic Centre for Science, Technology and Innovation in the field of ICT).  ... 
doi:10.1007/978-3-642-23641-9_8 fatcat:4fay4vdauvg2hbnbh6hehbu7oa

Extended Floating Car Data system - experimental study

R. Quintero, A. Llamazares, D. F. Llorca, M. A. Sotelo, L. E. Bellot, O. Marcos, I. G. Daza, C. Fernandez
2011 2011 IEEE Intelligent Vehicles Symposium (IV)  
Besides the stereo pair of cameras, the vehicle is equipped with a low-cost GPS and an electronic device for CAN Bus interfacing.  ...  The detection component implies the use of previously monocular approaches developed by our group in combination with new stereo vision algorithms that add robustness to the detection and increase the  ...  In order to define the SVM decision thresholds we use the ROC curves defining the work points in terms of the relationship between the Detection Rate (DR) and the False Positive Rate (FPR).  ... 
doi:10.1109/ivs.2011.5940444 dblp:conf/ivs/MinguezLLSCMDL11 fatcat:3j7m5wetzbcsflfka4oxf6qmky

Tunnel Facility-based Vehicle Localization in Highway Tunnel using 3D LIDAR [article]

Kyuwon Kim, Junhyuck Im, Gyuin Jee
2020 arXiv   pre-print
Therefore, it is a suitable localization method for highway tunnels where the feature points are few. The tunnel facility points were extracted using 3D LIDAR.  ...  Vehicle localization in highway tunnels is a challenging issue for autonomous vehicle navigation.  ...  If inconsistencies occur, the tunnel wall cannot be removed effectively from the point cloud, and it may cause false detection of tunnel facility points.  ... 
arXiv:2012.13168v1 fatcat:dcsdk3dig5bdvj5fltbzrkrg4y

Security Analysis of Camera-LiDAR Fusion Against Black-Box Attacks on Autonomous Vehicles [article]

R. Spencer Hallyburton, Yupei Liu, Yulong Cao, Z. Morley Mao, Miroslav Pajic
2022 arXiv   pre-print
Sensor fusion with multi-frame tracking is becoming increasingly popular for detecting 3D objects.  ...  To enable safe and reliable decision-making, autonomous vehicles (AVs) feed sensor data to perception algorithms to understand the environment.  ...  objects (i.e., false positive) [8, 40] , and remove existing objects (i.e., false negative) [5, 41] , each with devastating consequences at the driving decision and control level.  ... 
arXiv:2106.07098v4 fatcat:onalm73kcjdunoeqbzv4sscj7m

Automatic Grapevine Trunk Detection on UAV-Based Point Cloud

Juan M. Jurado, Luís Pádua, Francisco R. Feito, Joaquim J. Sousa
2020 Remote Sensing  
In this study, an automatic method for grapevine trunk detection, using 3D point cloud data, is presented.  ...  In the last few years, Unmanned Aerial Vehicles (UAVs) have become one of the main sources of remote sensing information for Precision Viticulture (PV) applications.  ...  TP: true positive; FP: false positive; TN: true negative; FN: false negative.  ... 
doi:10.3390/rs12183043 fatcat:sbmhzdc3lvc4bbe7maz42uu5wu


Samed ÖZDEMİR, Zeynep AKBULUT, Fevzi KARSLI, Hayrettin ACAR
2021 International Journal of Engineering and Geosciences  
Thanks to the high 3D resolution provided by the Light Detection and Ranging (LiDAR) point cloud, it has provided great convenience in complex 3D modeling processes needed for forestry applications such  ...  LiDAR data provides a new dimension in forestry applications with its high 3D resolution and multiple return characteristics.  ...  in the reference that is classified as background, FP (false positive) refers to an entity classified as an object that does not correspond to an object in the reference and TN (true negative) refers  ... 
doi:10.26833/ijeg.668352 fatcat:d7rw5mo35ngxrdqat2fi3rh3xy

Automated Reconstruction of Building LoDs from Airborne LiDAR Point Clouds Using an Improved Morphological Scale Space

Bisheng Yang, Ronggang Huang, Jianping Li, Mao Tian, Wenxia Dai, Ruofei Zhong
2016 Remote Sensing  
The previous methods reconstruct building LoDs from the finest 3D building models rather than from point clouds, resulting in heavy costs and inflexible adaptivity.  ...  Therefore, this paper proposes a novel method to reconstruct buildings at different LoDs from airborne Light Detection and Ranging (LiDAR) point clouds based on an improved morphological scale space.  ...  Jianping Li implemented the regularization of the outline for each building. Mao Tian performed the study of scale-space. Wenxia Dai and Ruofei Zhong implemented the segmentation of roof facets.  ... 
doi:10.3390/rs9010014 fatcat:65yltvgwn5fpthkkprrh3v5pfu


I. Gutierrez, E. Før Gjermundsen, W. D. Harcourt, M. Kuschnerus, F. Tonion, T. Zieher
2020 ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
However, it is necessary to classify the 3D point clouds into vegetation and bare-earth points using filtering algorithms so that changes caused by landslide activity can be quantified.  ...  An optimal set of parameters is derived for each algorithm and their performances are evaluated using different metrics.  ...  We further thank Jan Pfeiffer and Daniel Wujanz for providing the TLS data acquired in June 2017.  ... 
doi:10.5194/isprs-annals-v-2-2020-719-2020 fatcat:mnek6fg57ndqlfylpkm7zfqelm

Ground Penetrating Radar as a Contextual Sensor for Multi-Sensor Radiological Characterisation

Ikechukwu Ukaegbu, Kelum Gamage
2017 Sensors  
Consequently, this paper also examines ground-penetrating radar (GPR) as a contextual sensor for characterising this category of wastes and proposes several ways of integrating data from GPR and radiological  ...  Radioactive sources exist in environments or contexts that influence how they are detected and localised.  ...  The left images are for a vehicle with a source, and the right are for a vehicle without a source [26] .  ... 
doi:10.3390/s17040790 pmid:28387706 pmcid:PMC5422063 fatcat:brlzwclferdtfc3uybvte3xq4y

Beyond 2D landslide inventories and their rollover: synoptic 3D inventories and volume from repeat lidar data

Thomas G. Bernard, Dimitri Lague, Philippe Steer
2021 Earth Surface Dynamics  
To address these issues, we propose a new semiautomatic 3D point cloud differencing method to detect geomorphic changes, filter out false landslide detections due to lidar elevation errors, obtain robust  ...  In a 5 km2 area, the 3D point cloud differencing method detects 1118 potential sources.  ...  We also wish to thank the editors, Giulia Sofia and Niel Hovius, for their time and feedback.  ... 
doi:10.5194/esurf-9-1013-2021 fatcat:yt6ecvpvmfcn3ccffn4yorpoem
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