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Dynamic Belief Fusion for Object Detection [article]

Ryan Robinson
2015 arXiv   pre-print
A novel approach for the fusion of detection scores from disparate object detection methods is proposed.  ...  The proposed fusion method, called Dynamic Belief Fusion (DBF), dynamically assigns basic probabilities to propositions (target, non-target, uncertain) based on confidence levels in the detection results  ...  Dynamic Belief Fusion Overview of the Fusion of Detectors The objective of object detection is to localize each target object in an image.  ... 
arXiv:1502.07643v3 fatcat:gf2j6mvoirenzbmujoxawqhgw4

Dynamic Belief Fusion for Object Detection [article]

Hyungtae Lee, Heesung Kwon, Ryan M. Robinson, William d. Nothwang, and Amar M. Marathe
2015 arXiv   pre-print
A novel approach for the fusion of heterogeneous object detection methods is proposed.  ...  The main contribution of the proposed work is a novel fusion method, called Dynamic Belief Fusion (DBF), which dynamically assigns probabilities to hypotheses (target, non-target, intermediate state (target  ...  Conclusions A novel fusion method, referred to as Dynamic Belief Fusion (DBF), is proposed to improve upon current late fusion methods in the context of object detection.  ... 
arXiv:1511.03183v1 fatcat:5umpydybpnczlldrvzpzbozhva

DBF: Dynamic Belief Fusion for Combining Multiple Object Detectors

Hyungtae Lee, Heesung Kwon
2019 IEEE Transactions on Pattern Analysis and Machine Intelligence  
In this paper, we propose a novel and highly practical score-level fusion approach called dynamic belief fusion (DBF) that directly integrates inference scores of individual detections from multiple object  ...  for the fusion.  ...  The final output of the fusion process is a consolidated set of detections, each with a fused detection score. Dynamic Belief Fusion Object Detection Hypotheses.  ... 
doi:10.1109/tpami.2019.2952847 pmid:31722478 fatcat:mj7r4wdjlfeibkkdcd4u3rcpx4

Enhanced Object Detection via Fusion With Prior Beliefs from Image Classification [article]

Yilun Cao and Hyungtae Lee and Heesung Kwon
2016 arXiv   pre-print
A recently introduced novel fusion approach called dynamic belief fusion (DBF) is used to fuse the detector output with the classification prior.  ...  In this paper, we introduce a novel fusion method that can enhance object detection performance by fusing decisions from two different types of computer vision tasks: object detection and image classification  ...  [11] called Dynamic Belief Fusion (DBF) is used to build a probabilistic fusion model.  ... 
arXiv:1610.06907v1 fatcat:pubi5cg5evboddyr27sa52t6da

An Evidential Filter for Indoor Navigation of a Mobile Robot in Dynamic Environment [chapter]

Quentin Labourey, Olivier Aycard, Denis Pellerin, Michèle Rombaut, Catherine Garbay
2016 Communications in Computer and Information Science  
Robots are destined to live with humans and perform tasks for them. In order to do that, an adapted representation of the world including human detection is required.  ...  This article presents the key-stages of the multimodal fusion: an evidential grid is built from each modality using a modified Dempster combination, and a temporal fusion is made using an evidential filter  ...  The sensor grid cannot add belief on dynamic hypotheses as sensors are not able to detect motion in the scene. This can be done by detecting changes in the scene between the time t-1 and time t.  ... 
doi:10.1007/978-3-319-40596-4_25 fatcat:lf6tn5il6ffgdleedug4x6f37a

Titelei/Inhaltsverzeichnis [chapter]

Michael Aeberhard
2017 Object-Level Fusion for Surround Environment Perception in Automated Driving Applications  
In this thesis, an environment model approach for the detection of dynamic objects is presented in order to realize an effective method for sensor data fusion.  ...  The work presented in this thesis has been extensively used in several research projects as the dynamic object detection platform for automated driving applications on highways in real traffic.  ...  Detection . . . . . . . . . . . . . . . . . . . . . . . . . . 21 1.4 Contribution and Outline of the Thesis . . . . . . . . . . . . . . . . . . . . 23 2 Sensor Data Fusion Architectures 27 2.1 Overview  ... 
doi:10.51202/9783186804129-i fatcat:lpn7w4g7vngdpcegh5tpefx3hy

Evidence Reasoning Machine based on DSmT for mobile robot mapping in unknown dynamic environment

Xinhan Huang, Peng Li, Min Wang
2009 2009 IEEE International Conference on Robotics and Biomimetics (ROBIO)  
Meanwhile a few of general basic belief assignment functions (gbbaf) are constructed for fusion. Finally, map building experiment is carried out with Pioneer 2-DXe mobile robot.  ...  And then the Evidence Reasoning Machine (ERM) based on DSmT is presented for mobile robot mapping in unknown dynamic environment.  ...  Sonar sensor modeling for DSmT The simple principle of sonar sensor is: it generates sheaves of cone-shaped wave to detect the objects. The wave will be reflected as soon as it encounters an object.  ... 
doi:10.1109/robio.2009.5420580 dblp:conf/robio/HuangLW09 fatcat:x44lxut3dfgwriwyl5wilnk5am

Context-based multi-level information fusion for harbor surveillance

Juan Gómez-Romero, Miguel A. Serrano, Jesús García, José M. Molina, Galina Rogova
2015 Information Fusion  
This paper proposes a fusion system for context-based situation and threat assessment with application to harbor surveillance. The architecture of the system is organized in two levels.  ...  The higher level applies Belief-based Argumen-tation to evaluate the threat posed by suspicious vessels.  ...  Object property estimation for object categorization.  ... 
doi:10.1016/j.inffus.2014.01.011 fatcat:h6x57el34rgq7nz5bzakvzdliu

Distributed inference in wireless sensor networks

V. V. Veeravalli, P. K. Varshney
2011 Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences  
In particular, results on distributed detection, parameter estimation and tracking in WSNs will be discussed, with a special emphasis on solutions to these inference problems that take into account the  ...  The authors would like to thank Dr Engin Masazade for his help with the preparation of this paper.  ...  Such a control problem was studied by Castanon [113] in the context of classification of a large number of unknown objects, where an approximate dynamic programming approach for dynamic scheduling of  ... 
doi:10.1098/rsta.2011.0194 pmid:22124084 fatcat:jtwubvrlnnfgpkcu46jvqim3ra

Grid occupancy estimation for environment perception based on belief functions and PCR6

Julien Moras, Jean Dezert, Benjamin Pannetier, Ivan Kadar
2015 Signal Processing, Sensor/Information Fusion, and Target Recognition XXIV  
So far, the estimation and the grid map updating have been done using fusion techniques based on the probabilistic framework, or on the classical belief function framework thanks to an inverse model of  ...  classical belief-based approaches.  ...  The map grid acts as a filter that accumulate information and allows to detect moving objects.  ... 
doi:10.1117/12.2177653 fatcat:pet6hksqanavjayabmwc4rkqkm

Object tracking and dynamic estimation on evidential grids

Ruben Jungnickel, Franz Korf
2014 17th International IEEE Conference on Intelligent Transportation Systems (ITSC)  
We reduce false positives and initialization time by maintaining a dynamic belief for each object.  ...  Taking advantage of the Dempster Shafer theory, a dynamic belief of conflicting cells can be estimated. This dynamic belief is then accumulated in a tracked object model.  ...  The main contribution of this paper is the detection and modelling of dynamic objects as grid cells maintaining a dynamic beliefs mass based on DST.  ... 
doi:10.1109/itsc.2014.6958060 dblp:conf/itsc/JungnickelK14 fatcat:zkppdi5kj5hsvdu5qo73tyvnv4

A Method to Determine Basic Probability Assignment in Context Awareness of a Moving Object

Donghyok Suh, Juhye Yook
2013 International Journal of Distributed Sensor Networks  
This was used to determine BPA for multi-sensor data fusion so that a pedestrian, who walked or moved, could recognize a moving object.  ...  The study showed that a pedestrian could recognize a moving object with the method of determining BPA through multi-sensor data fusion conducted in the study.  ...  Table 2 shows that BPA could be calculated by using variation rates in time intervals and used for calculating belief and uncertainty in each focal element resulted from data fusion for context inference  ... 
doi:10.1155/2013/972641 fatcat:ld3fkgecqnhs5mha2wwcbwse3e

Multisensor Data Fusion Based on Modified Belief Entropy in Dempster–Shafer Theory for Smart Environment

Ihsan Ullah, Joosang Youn, Youn-Hee Han
2021 IEEE Access  
However, sensors provide noisy and uncertain information which is a big challenge for researchers. Since uncertainty in the data is a central constraint for data fusion and decision-making systems.  ...  INDEX TERMS Multisensor data fusion, Dempster-Shaffer theory, uncertainty measurements, belief entropy, wireless sensor network.  ...  Figure 7 shows the fusion results for six different objects by combining BoEs from different sensors. Believes are distributed for different objects.  ... 
doi:10.1109/access.2021.3063242 fatcat:v73vg7vb7jdv7ipk4evhbkx3j4

Environment Perception Using Grid Occupancy Estimation With Belief Functions

Jean Dezert, Julien Moras, Benjamin Pannetier
2015 Zenodo  
It will play a major role for the safety (obstacle avoidance) of next generations of terrestrial vehicles, as well as for future autonomous navigation systems.  ...  The state of each cell must be estimated from sensors measurements and classified in order to get a complete and precise perception of the dynamic environment where the vehicle moves.  ...  Like the averaging fusion rule, the PCR6 fusion rule is commutative but not associative. The vacuous belief assignment is a neutral element for this rule.  ... 
doi:10.5281/zenodo.23208 fatcat:i6yv32fmqjcqlnkc4idn43wq5q

Data fusion to improve trajectory tracking in a Cooperative Surveillance Multi-Agent Architecture

Federico Castanedo, Jesús García, Miguel A. Patricio, José M. Molina
2010 Information Fusion  
We show how the inclusion of this new dynamic local fusion agent guarantee that, in a video-surveillance system, objects of interest are successfully tracked across the whole area, assuring continuity  ...  ), local layer within coalitions, with the dynamic instantiation of a local fusion agent.  ...  When the fusion center agent detects deviations in the tracking process or when an object could be tracked by two or more agents, a local fusion agent is dynamically created by the fusion center agent.  ... 
doi:10.1016/j.inffus.2009.09.002 fatcat:mzaqaqxd4fgsjksemqbidvtwmi
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