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Research and Design on Vehicle Pedestrian Detection in Natural Scene
2018
DEStech Transactions on Computer Science and Engineering
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We propose a two-layer pedestrian feature extraction algorithm based on multi features fusion in integral channel, which is gained by intelligent driving system in natural environment. ...
While ensuring real-time detection, we improved the low robustness of single layer features. ...
Summary This paper makes improvement based on integral image technology, presents a double layer pedestrian detection algorithm based on multi feature fusion is a kind of integral channel. ...
doi:10.12783/dtcse/cmee2017/20042
fatcat:dxi5ixajljdpfm563kgh6kfik4
Review of Data Fusion Methods for Real-Time and Multi-Sensor Traffic Flow Analysis
2021
IEEE Access
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[38] suggest a hybrid method based on deep feature fusion modeling to achieve speed prediction. ...
[74] propose a robust travel-time estimation method based on license plate recognition, geomagnetic detector data, and floating car data as traffic data input. Zhang et al. ...
doi:10.1109/access.2021.3069770
fatcat:2p52c7psrzhofgy4l2jy5fxw4u
OLIMP: A Heterogeneous Multimodal Dataset for Advanced Environment Perception
2020
Electronics
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Recent improvements and breakthroughs in scene understanding for intelligent transportation systems are mainly based on deep learning and the fusion of different modalities. ...
In this context, we introduce OLIMP: A heterOgeneous Multimodal Dataset for Advanced EnvIronMent Perception. ...
Afterwards, features are concatenated via VoxelNet architecture. In [33] an architecture based on two single stage detector is proposed. ...
doi:10.3390/electronics9040560
fatcat:m7xosqzegbgfnabzqzp3n2gagy
Belief Function Definition for Ensemble Methods - Application to Pedestrian Detection in Dense Crowds
2018
2018 21st International Conference on Information Fusion (FUSION)
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Fusion In order to perform the fusion of detectors based on different features, there exist in the literature various approaches depending on the considered problem. ...
In the context of high-density crowd pedestrian detection, in [3] we propose a robust fusion strategy also based on the belief functions framework, that is able to take into account the spatial imprecision ...
doi:10.23919/icif.2018.8455313
dblp:conf/fusion/VandoniHA18
fatcat:5zvr6quhevgfjcl5hpfzxlwcdq
Multi-Cue Event Information Fusion for Pedestrian Detection With Neuromorphic Vision Sensors
2019
Frontiers in Neurorobotics
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We demonstrate the advantages of the decision-level fusion via leveraging multi-cue event information and show that our approach performs well on a self-annotated event-based pedestrian dataset with 8,736 ...
In this work, we propose to develop pedestrian detectors that unlock the potential of the event data by leveraging multi-cue information and different fusion strategies. ...
It is expected that the pedestrian detector based on such merged data could enjoy better adaptability and robustness with a higher average detection precision. ...
doi:10.3389/fnbot.2019.00010
pmid:31001104
pmcid:PMC6454154
fatcat:ghcpudwcjjdixny2ysjvondyx4
Robust Deep Multi-modal Learning Based on Gated Information Fusion Network
[article]
2018
arXiv
pre-print
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improvement based on Single Shot Detector (SSD) for KITTI dataset using the proposed fusion network and data augmentation schemes. ...
In order to facilitate the robustness to the degraded modalities, we employ the gated information fusion (GIF) network which weights the contribution from each modality according to the input feature maps ...
In Section 2, we review the previous literature on the DML. In Section 3, we present the details on the proposed GIF network and the robust 2D object detector based on multi-modal fusion. ...
arXiv:1807.06233v2
fatcat:hf24etcq6be4bjjfisk36wqdlm
An evidential framework for pedestrian detection in high-density crowds
2017
2017 14th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)
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We propose an evidential fusion algorithm which is able to exploit multiple detectors based on different gradient, texture and orientation descriptors. ...
Moreover, the proposed algorithm outperforms a fusion solution based on Multiple Kernel Learning on difficult high-density crowd images acquired at Makkah at the height of the Muslim pilgrimage. ...
Fusion Regarding the fusion of detectors based on different features, some fundamentally different approaches are popular in the literature for the pedestrian detection task. ...
doi:10.1109/avss.2017.8078498
dblp:conf/avss/VandoniAH17
fatcat:koncadx2cjekllzfn6tvqn3tdq
DeepFusion: Lidar-Camera Deep Fusion for Multi-Modal 3D Object Detection
[article]
2022
arXiv
pre-print
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Based on InverseAug and LearnableAlign, we develop a family of generic multi-modal 3D detection models named DeepFusion, which is more accurate than previous methods. ...
However, as those features are often augmented and aggregated, a key challenge in fusion is how to effectively align the transformed features from two modalities. ...
Based on these techniques, we develop a family of simple, generic, yet effective multi-modal 3D detectors, named DeepFusions, which achieves state-of-theart performance on the Waymo Open Dataset. on 3D ...
arXiv:2203.08195v1
fatcat:ehhtpds7cvexrnnlw5hccmegbq
Pedestrian Detection in Far-Infrared Daytime Images Using a Hierarchical Codebook of SURF
2015
Sensors
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Our system consists of three modules, each based on speeded-up robust feature (SURF) matching. ...
In this paper, we propose a pedestrian detector with on-board FIR camera. ...
The plotting results on our testing dataset show that our detector based on the HC of SURF features (HCS) outperforms the state-of-the-art pedestrian detectors: VJ, HOG and MultiFtr. ...
doi:10.3390/s150408570
pmid:25871724
pmcid:PMC4431237
fatcat:5s44rufhdbdytjyxb4uvzibz3i
MLOD: A multi-view 3D object detection based on robust feature fusion method
2019
2019 IEEE Intelligent Transportation Systems Conference (ITSC)
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Hence the object detector can be trained on data labelled in different views to avoid the degeneration of feature extractors. ...
The fusion of image and BEV features is challenging, as they are derived from different perspectives. ...
[20] proposed a method that projects image features into BEV and fuses them with the convolutional layers of a LIDAR based detector using a continuous fusion layer (see Figure 2 .13). ...
doi:10.1109/itsc.2019.8917126
dblp:conf/itsc/DengC19
fatcat:kp7ablx24bfzvev5hihvcc6pcq
Heterogeneous Gray-Temperature Fusion-Based Deep Learning Architecture for Far Infrared Small Target Detection
2019
Journal of Sensors
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This paper proposes a novel deep learning-based far infrared small target detection method and a heterogeneous data fusion method to solve the lack of semantic information due to the small target size. ...
The experimental results showed that there is a significant difference in performance according to the various fusion methods and normalization methods, and the proposed detector showed approximately 20% ...
Figure 9 : 9 Figure 9: Comparison of the results of proposed deep learning based detector, conventional CFAR detector, and HB-based detector.The proposed detector is based on the fusion method using two ...
doi:10.1155/2019/4658068
fatcat:b26vferrlzeyblj4ijooulp7u4
Person search: New paradigm of person re-identification: A survey and outlook of recent works
2020
Image and Vision Computing
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This survey paper includes brief discussion about feature representation learning and deep metric learning with novel loss functions. ...
We thoroughly review datasets with performance analysis on existing datasets. Finally, we are reviewing current solutions for further consideration. ...
To focus on those areas where pedestrian gather in a scene, pedestrian detector Faster-RCNN modified and implemented structure-aware anchors in detector. ...
doi:10.1016/j.imavis.2020.103970
fatcat:g2zuqww7tbdszkxrc2wkrfno2y
Learning Cross-Modal Deep Representations for Robust Pedestrian Detection
[article]
2018
arXiv
pre-print
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Our approach relies on a novel cross-modality learning framework and it is based on two main phases. ...
In this way, features which are both discriminative and robust to bad illumination conditions are learned. ...
Differently from previous deep learning models addressing the occlusion problem, DeepParts does not rely on a single detector but it is based on multiple part detectors. Tian et al. ...
arXiv:1704.02431v2
fatcat:keuvqg4dfzbu3e6h4eemrcj34e
Query Adaptive Late Fusion for Image Retrieval
[article]
2018
arXiv
pre-print
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In the learning version, it can also be applied to supervised tasks like person recognition and pedestrian retrieval, based on a trainable neural module. ...
Feature fusion is a commonly used strategy in image retrieval tasks, which aggregates the matching responses of multiple visual features. ...
We use the part-based convolutional baseline (PCB) [31] as the pedestrian descriptor, which outputs six part-based features for a pedestrian image. ...
arXiv:1810.13103v1
fatcat:3rvbbzxgg5cvbmmvz4ar3jlsmq
Learning Cross-Modal Deep Representations for Robust Pedestrian Detection
2017
2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
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Our approach relies on a novel cross-modality learning framework and it is based on two main phases. ...
In this way, features which are both discriminative and robust to bad illumination conditions are learned. ...
Differently from previous deep learning models addressing the occlusion problem, DeepParts does not rely on a single detector but it is based on multiple part detectors. Tian et al. ...
doi:10.1109/cvpr.2017.451
dblp:conf/cvpr/XuORWS17
fatcat:dx3gluuoffdklouxprura6zaty
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