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Scene-Specific Pedestrian Detection Based on Parallel Vision [article]

Wenwen Zhang, Kunfeng Wang, Hua Qu, Jihong Zhao, Fei-Yue Wang
2017 arXiv   pre-print
In this paper, we propose an ACP-based method, with augmented reality's help, we build the virtual world of specific scenes, and make people walking in the virtual scenes where it is possible for them  ...  to appear to solve this problem of lacking labeled data and the results show that data from virtual world is helpful to adapt generic pedestrian detectors to specific scenes.  ...  RELATED WORK As a part of ACP method,the virtual scene, also as virtual world is important.  ... 
arXiv:1712.08745v1 fatcat:y6f3iuo5hbh3vmbq5ftf5sczte

Learning a multiview part-based model in virtual world for pedestrian detection

Jiaolong Xu, David Vazquez, Antonio M. Lopez, Javier Marin, Daniel Ponsa
2013 2013 IEEE Intelligent Vehicles Symposium (IV)  
In this paper, we propose to train a multiview deformable part-based model with automatically generated part examples from virtual-world data.  ...  The method is efficient as: (i) the part detectors are trained with precisely extracted virtual examples, thus no latent learning is needed, (ii) the multiview pedestrian detector enhances the performance  ...  CONCLUSION In this paper we have presented a method to train a multiview deformable part-based model with virtual-world data for pedestrian detection.  ... 
doi:10.1109/ivs.2013.6629512 dblp:conf/ivs/XuVLMP13 fatcat:5skx3sik45athek27f4diykz5i

Learning appearance in virtual scenarios for pedestrian detection

Javier Marin, David Vazquez, David Geronimo, Antonio M. Lopez
2010 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition  
The most promising detectors rely on appearance-based pedestrian classifiers trained with labelled samples.  ...  We test such classifiers in a publicly available dataset provided by Daimler AG for pedestrian detection benchmarking. This dataset contains real world images acquired from a moving car.  ...  Conclusions In this paper we have explored how realistic virtual worlds can help in learning appearance-based models for pedestrian detection in the ADAS area.  ... 
doi:10.1109/cvpr.2010.5540218 dblp:conf/cvpr/MarinVGL10 fatcat:a7e3ocrplbgejbdmm6g6niuvzq

Weakly Supervised Automatic Annotation of Pedestrian Bounding Boxes

David Vazquez, Jiaolong Xu, Sebastian Ramos, Antonio M. Lopez, Daniel Ponsa
2013 2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops  
In particular, we train a pedestrian classifier based on virtual-world samples (no human annotation required).  ...  However, learning from virtual-world samples and testing in real-world images may suffer the dataset shift problem.  ...  The idea is that at the end of the process we can end up with a large number of real-world pedestrian BBs without manually an- notating them, i.e. the virtual-world-based pedestrian detector provides BBs  ... 
doi:10.1109/cvprw.2013.107 dblp:conf/cvpr/VazquezXRLP13 fatcat:5b657dmquvbcpdhyg6wyuk4r6y

Virtual and Real World Adaptation for Pedestrian Detection

David Vazquez, Antonio M. Lopez, Javier Marin, Daniel Ponsa, David Geronimo
2014 IEEE Transactions on Pattern Analysis and Machine Intelligence  
Thus, we face the question: can a pedestrian appearance model learnt in realistic virtual worlds work successfully for pedestrian detection in realworld images?.  ...  with the many examples of the source domain (virtual world) in order to train a domain adapted pedestrian classifier that will operate in the target domain.  ...  Analogously, we can learn a part-based pedestrian classifier with dense descriptors [20] , or using the pedestrian silhouette instead [21] .  ... 
doi:10.1109/tpami.2013.163 pmid:26353201 fatcat:igb6ie7fcfcblldqxyiu4ymepm

Domain Adaptation of Deformable Part-Based Models

Jiaolong Xu, Sebastian Ramos, David Vazquez, Antonio M. Lopez
2014 IEEE Transactions on Pattern Analysis and Machine Intelligence  
Index Terms-domain adaptation, deformable part-based model, pedestrian detection ✦ This is the author's version of an article that has been published in this journal.  ...  By taking into account the inherent structure in feature space (e.g., the parts in a DPM), we propose a structure-aware A-SSVM (SA-SSVM).  ...  The figure shows the adaptation of a DPM-based pedestrian detector from a virtual-world source domain to a real-world target domain.  ... 
doi:10.1109/tpami.2014.2327973 pmid:26353145 fatcat:5c6tlp4vmnf3vpwe4elewdmzay

From Virtual to Real World Visual Perception using Domain Adaptation -- The DPM as Example [article]

Antonio M. Lopez, Jiaolong Xu, Jose L. Gomez, David Vazquez, German Ros
2016 arXiv   pre-print
In this chapter we revisit the DA of a deformable part-based model (DPM) as an exemplifying case of virtual- to-real-world DA.  ...  in the virtual world.  ...  Learning ference on Neural Information Processing Sys- a part-based pedestrian detector in a virtual tems (NIPS), Workshop on Domain  ... 
arXiv:1612.09134v1 fatcat:ky7jz3nvh5gkjaxe5npoztyooi

Learning scene-specific pedestrian detectors without real data

Hironori Hattori, Vishnu Naresh Boddeti, Kris Kitani, Takeo Kanade
2015 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)  
As a result, our method is able to learn a unique pedestrian classifier customized for every possible location in the scene.  ...  This scenario may arise when a new surveillance system is installed in a novel location and a scene-specific pedestrian detector must be trained prior to any observations of pedestrians.  ...  SSV: A single HOG+SVM based pedestrian detector trained only on virtual pedestrians whose appearance is simulated in the specific scene under consideration.  ... 
doi:10.1109/cvpr.2015.7299006 dblp:conf/cvpr/HattoriBKK15 fatcat:akli7fz3lvbvzanozub5kn67ku

Learning people detection models from few training samples

Leonid Pishchulin, Arjun Jain, Christian Wojek, Mykhaylo Andriluka, Thorsten Thormahlen, Bernt Schiele
2011 CVPR 2011  
In particular we employ a rendering-based reshaping method in order to generate thousands of synthetic training samples from only a few persons and views.  ...  State-of-the-art methods learn appearance based models requiring tedious collection and annotation of large data corpora.  ...  We would like to thank Javier Marin Tur for provided dataset of virtual pedestrians.  ... 
doi:10.1109/cvpr.2011.5995574 dblp:conf/cvpr/PishchulinJWATS11 fatcat:oesxilc4izfcpht56fdel6hlwi

Visual Compiler: Synthesizing a Scene-Specific Pedestrian Detector and Pose Estimator [article]

Namhoon Lee, Xinshuo Weng, Vishnu Naresh Boddeti, Yu Zhang, Fares Beainy, Kris Kitani, Takeo Kanade
2016 arXiv   pre-print
We introduce the concept of a Visual Compiler that generates a scene specific pedestrian detector and pose estimator without any pedestrian observations.  ...  Using these renders we learn a scene-and-region specific spatially-varying fully convolutional neural network, for simultaneous detection, pose estimation and segmentation of pedestrians.  ...  [29] combined synthetic pedestrian data with real pedestrian data to generate robust real world detectors. Pishchulin et al.  ... 
arXiv:1612.05234v1 fatcat:iwg7mrpt7jcjpe6wh5lsxtav2i

Using Synthetic Data to Improve and Evaluate the Tracking Performance of Construction Workers on Site

Marcel Neuhausen, Patrick Herbers, Markus König
2020 Applied Sciences  
Our approach is verified by means of a tracking system. For this, we train a YOLOv3 detector identifying pedestrian workers.  ...  Using 3D computer graphics software, we model virtual construction site scenarios. These are rendered for the use as a synthetic dataset which augments a self-recorded real world dataset.  ...  Acknowledgments: The motion capture data used in this project was obtained from mocap.cs.cmu.edu. The CMU database was created with funding from NSF EIA-0196217.  ... 
doi:10.3390/app10144948 fatcat:z5myerml3fcota6glvgqxfe4sm

Auto-Zooming CNN-Based Framework for Real-Time Pedestrian Detection in Outdoor Surveillance Videos

Saghir Alfasly, Beibei Liu, Yongjian Hu, Yufei Wang, Chang-Tsun Li
2019 IEEE Access  
This paper proposes a fast, lightweight, and auto-zooming-based framework for small pedestrian detection.  ...  We have compared our framework performance with different single-step customized pedestrian detectors as well as the two-step detector faster R-CNN.  ...  like to thank the graduate students: Xiangquan Chen, Xin LI, Yifei Gao, Yuyi Lin, Zeqiong Yu, Xin Luo, Kun Zhang, Qunqi Zeng, and Runze Chen for their contributions on annotating the utilized dataset in  ... 
doi:10.1109/access.2019.2931915 fatcat:ck4kai7ynzggxalwy6ku33itki

Instance Segmentation Method of User Interface Component of Games

Shinjin Kang, Jong-in Choi
2020 Applied Sciences  
A vision deep learning network exploits pure pixel information in the screen.  ...  In this paper, we propose a methodology that segments UI components in a game by using synthetic game images created on a game engine.  ...  In 2015, Ref. [ 43 ] proposed a deep learning-based face detector that determined the final face by separately detecting facial parts such as head, eyes, nose, mouth, and beard.  ... 
doi:10.3390/app10186502 fatcat:gxnwnfxetnbqvcjdvq24phqe4y

Self-Learning Scene-Specific Pedestrian Detectors Using a Progressive Latent Model

Qixiang Ye, Tianliang Zhang, Wei Ke, Qiang Qiu, Jie Chen, Guillermo Sapiro, Baochang Zhang
2017 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)  
In this paper, a self-learning approach is proposed towards solving scene-specific pedestrian detection problem without any human' annotation involved.  ...  Compared with conventional latent models, the proposed PLM incorporates a spatial regularization term to reduce ambiguities in object proposals and to enforce object localization, and also a graph-based  ...  Supervised-SLSV [19] : A state-of-the-art scene-specific pedestrian detector learned from virtual pedestrians whose appearance is simulated in the specific scene under consideration.  ... 
doi:10.1109/cvpr.2017.222 dblp:conf/cvpr/YeZKQCSZ17 fatcat:4b6uc7qvfvhkhj5gljgim5a7ai

Hierarchical Adaptive Structural SVM for Domain Adaptation [article]

Jiaolong Xu, Sebastian Ramos, David Vazquez, Antonio M. Lopez
2014 arXiv   pre-print
In the former we apply HA-SSVM to the deformable part-based model (DPM) while in the latter HA-SSVM is applied to multi-category classifiers.  ...  Altogether, we term our proposal as hierarchical A-SSVM (HA-SSVM). As proof of concept we use HA-SSVM for pedestrian detection and object category recognition.  ...  Caltech shows results of adapting virtual-world DPM detector to a multi-resolution detector in Caltech pedestrian dataset. A-SSVM is trained with mixed high and low resolution samples.  ... 
arXiv:1408.5400v1 fatcat:scinfinrfvga7nc5ag7xz4x6me
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