Filters








922 Hits in 4.5 sec

Object Tracking Using Multiple Neuromorphic Vision Sensors [chapter]

Vlatko Bečanović, Ramin Hosseiny, Giacomo Indiveri
2005 Lecture Notes in Computer Science  
In this paper we show how a combination of multiple neuromorphic vision sensors can achieve the same higher level visual processing tasks as carried out by a conventional vision system.  ...  We process the multiple neuromorphic sensory signals with a standard auto-regression method in order to fuse the sensory signals and to achieve higher level vision processing tasks at a very high update  ...  Alan Stocker, from the Center for Neural Science, New York University, for providing the 2D optical flow sensor. Special  ... 
doi:10.1007/978-3-540-32256-6_36 fatcat:sevrpia43vcbvgi6obfy5p6x4a

Neuromorphic Vision Based Multivehicle Detection and Tracking for Intelligent Transportation System

Guang Chen, Hu Cao, Muhammad Aafaque, Jieneng Chen, Canbo Ye, Florian Röhrbein, Jörg Conradt, Kai Chen, Zhenshan Bing, Xingbo Liu, Gereon Hinz, Walter Stechele (+1 others)
2018 Journal of Advanced Transportation  
Neuromorphic vision sensor is a new passive sensing modality and a frameless sensor with a number of advantages over traditional cameras.  ...  In this paper, we propose the first neuromorphic vision based multivehicle detection and tracking system in ITS.  ...  (c) Miniature Embedded Dynamic Vision Sensor (meDVS). (d) Dynamic and Active Pixel Vision Sensor (DAVIS). This figure is adopted from [11] . (i) MOTA(↑): Multiple Object Tracking Accuracy.  ... 
doi:10.1155/2018/4815383 fatcat:a4jmeozosjg5zpx6jfdwovmvcm

Real-time Tracking Based on Neuromrophic Vision [article]

Hongmin Li, Pei Jing, Guoqi Li
2015 arXiv   pre-print
Our method demonstrates that the computer vision methods could be used for the neuromorphic vision processing and we can realize fast real-time tracking using neuromorphic vision sensors compare to the  ...  Neuromorphic vision is a concept defined by incorporating neuromorphic vision sensors such as silicon retinas in vision processing system.  ...  Tracking Algorithm In this section, we summarize the compressive tracking algorithm we used in the neuromorphic vision tracking problem based on the appearance of objects in spike count coding as is shown  ... 
arXiv:1510.05275v1 fatcat:l4advmyxt5efze5jjjxwzb2gue

Robot Soccer using Optical Analog VLSI Sensors

V. Bečanović, R. Hosseiny, G. Indiveri
2004 International Journal of Robotics and Automation  
In this paper we show how a combination of low dimensional vision sensors can be used to aid the higher level visual processing task of colour blob tracking, carried out by a conventional vision system  ...  robot, then, we process the multiple neuromorphic sensory signals with a standard auto-regression method in order to achieve a higher level vision processing task at a much higher update rate.  ...  Alan Stocker, from the Centre for Neural Science, New York University, for providing the 2D optical flow sensor. Special thanks are due to Stefan Kubina, Adriana Arghir, Dr. Horst Günther and Dr.  ... 
doi:10.2316/journal.206.2004.4.206-2718 fatcat:xh4gxm2r6bhvhkdadxkaa6zth4

DVS Benchmark Datasets for Object Tracking, Action Recognition, and Object Recognition

Yuhuang Hu, Hongjie Liu, Michael Pfeiffer, Tobi Delbruck
2016 Frontiers in Neuroscience  
Neuromorphic vision uses silicon retina sensors such as the dynamic vision sensor (DVS; Lichtsteiner et al., 2008) .  ...  We have explicitly chosen mostly dynamic vision tasks such as action recognition or tracking, which could benefit from the strengths of neuromorphic vision sensors, although algorithms that exploit these  ...  Neuromorphic vision uses silicon retina sensors such as the dynamic vision sensor (DVS; Lichtsteiner et al., 2008) .  ... 
doi:10.3389/fnins.2016.00405 pmid:27630540 pmcid:PMC5006598 fatcat:jq2al6tmjjagtj633id7twtvqm

ROBOTIC VISION:Neuromorphic Vision Sensors

G. Indiveri
2000 Science  
Using these methods, significant progress has been made on vision problems such as threedimensional (3D) scene reconstruction, object recognition, texture analysis and synthesis, and tracking (1, 2).  ...  Digital vision sensors.  ...  We acknowledge the contributions of our colleagues at the Institute of Neuroinformatics and the Telluride Workshop on Neuromorphic Engineering.  ... 
doi:10.1126/science.288.5469.1189 pmid:10841740 fatcat:ksnqk6ozr5efdp6buwpsleug5i

Event-Based Attention and Tracking on Neuromorphic Hardware

Alpha Renner, Matthew Evanusa, Yulia Sandamirskaya
2019 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)  
We present a fully event-driven vision and processing system for selective attention and tracking, realized on a neuromorphic processor Loihi interfaced to an event-based Dynamic Vision Sensor DAVIS.  ...  We demonstrate capability of the system to create sustained activation that supports object tracking when distractors are present or when the object slows down or stops, reducing the number of generated  ...  Julien Martel and the Intel Neuromorphic Computing Lab for their help with the hardware and software setup used in this work.  ... 
doi:10.1109/cvprw.2019.00220 dblp:conf/cvpr/RennerES19 fatcat:544tqwjimza5do4l2y7z5knfoi

A low-power end-to-end hybrid neuromorphic framework for surveillance applications [article]

Andres Ussa, Luca Della Vedova, Vandana Reddy Padala, Deepak Singla, Jyotibdha Acharya, Charles Zhang Lei, Garrick Orchard, Arindam Basu and Bharath Ramesh
2020 arXiv   pre-print
To address this challenge, this paper proposes a low-power (5W) end-to-end neuromorphic framework for object tracking and classification using event-based cameras that possess desirable properties such  ...  Finally, we compare the proposed methodologies to state-of-the-art event-based systems for object tracking and classification, and demonstrate the use case of our neuromorphic approach for low-power applications  ...  The dominant approach in the literature for object tracking and detection using neuro- morphic vision sensors has been an event-by-event approach [10, 16, 21].  ... 
arXiv:1910.09806v3 fatcat:srfubucpg5e7robg2x2jbjmuxy

Neuromorphic vision chips

Nanjian Wu
2018 Science China Information Sciences  
The ED neuromorphic vision chip system is based on address-event-representation image sensor and event-driven multi-kernel convolution network.  ...  The FD neuromorphic reconfigurable vision chip comprises a high speed image sensor, a processing element array and self-organizing map neural network.  ...  The chip can be applied to track multiple targets under different conditions. Figure 3 show the schematic diagram of the ED vision chip.  ... 
doi:10.1007/s11432-017-9303-0 fatcat:tnl2guf3yvczhgdlmkclhvgsqy

Event-based Robotic Grasping Detection with Neuromorphic Vision Sensor and Event-Stream Dataset [article]

Bin Li, Hu Cao, Zhongnan Qu, Yingbai Hu, Zhenke Wang, Zichen Liang
2020 arXiv   pre-print
To obtain more agile robotic perception, a neuromorphic vision sensor (DAVIS) attaching to the robot gripper is introduced to explore the potential usage in grasping detection.  ...  Compared to traditional frame-based computer vision, neuromorphic vision is a small and young community of research.  ...  CONCLUSION In this paper, we construct a dynamic robotic grasping dataset with 91 generic objects using neuromorphic vision sensor (DAVIS).  ... 
arXiv:2004.13652v2 fatcat:ek5zbnsmt5hb3nn4t2pkdwe3rm

Event-Based Robotic Grasping Detection With Neuromorphic Vision Sensor and Event-Grasping Dataset

Bin Li, Hu Cao, Zhongnan Qu, Yingbai Hu, Zhenke Wang, Zichen Liang
2020 Frontiers in Neurorobotics  
To obtain more agile robotic perception, a neuromorphic vision sensor (Dynamic and Active-pixel Vision Sensor, DAVIS) attaching to the robot gripper is introduced to explore the potential usage in grasping  ...  Compared to traditional frame-based computer vision, neuromorphic vision is a small and young community of research.  ...  CONCLUSION In this paper, we constructed a dynamic robotic grasping dataset using neuromorphic vision sensor (DAVIS), which contains around 91 generic objects.  ... 
doi:10.3389/fnbot.2020.00051 pmid:33162883 pmcid:PMC7580650 fatcat:pluc3yvf55daxaobxdemgiuifi

Neuromorphic sensory systems

Shih-Chii Liu, Tobi Delbruck
2010 Current Opinion in Neurobiology  
Neuromorphic sensors and sensory systems have made the greatest strides in recent years with many designs using a new form of asynchronous output representation which carries timing information similar  ...  Experiments using these sensors can impact how we think the brain processes sensory information.  ...  Baker; and the NSF Telluride Neuromorphic Cognitive Engineering Workshop.  ... 
doi:10.1016/j.conb.2010.03.007 pmid:20493680 fatcat:zgtlwtysj5e25pp5ejrsctd4tu

Event-Based Sensing and Signal Processing in the Visual, Auditory, and Olfactory Domain: A Review

Mohammad-Hassan Tayarani-Najaran, Michael Schmuker
2021 Frontiers in Neural Circuits  
We also provide a survey of the literature covering neuromorphic sensing and signal processing in all three modalities.  ...  The key principle pursued in neuromorphic sensing is to shed the traditional approach of periodic sampling in favor of an event-driven scheme that mimicks sampling as it occurs in the nervous system, where  ...  Multiple Object Tracking Some works targeted specifically multiple object tracking, for example, Gómez-Rodríguez et al. (2010) that presents a cascade architecture for that purpose.  ... 
doi:10.3389/fncir.2021.610446 pmid:34135736 pmcid:PMC8203204 fatcat:qjvv6czzufazthcyvs7go5pnj4

Autonomous vehicle guidance using analog VLSI neuromorphic sensors [chapter]

Giacomo Indiveri, Paul Verschure
1997 Lecture Notes in Computer Science  
We present data both from the neuromorphic sensor and from the overall system, performing a line tracking task.  ...  Specifically, we demonstrate how the real-time visual pre-processing capabilities of the neuromorphic sensor are instrumental in enabling the system to reliably and autonomously track a continuous edge  ...  This work was inspired by the 1996 Telluride Workshop on Neuromorphic Engineering (funded by the U.S. NSF and the Gatsby Foundation) and was supported by the Swiss National Science Foundation.  ... 
doi:10.1007/bfb0020254 fatcat:anfjwhnxvzgg3ivamen5l5ke7q

EBBIOT: A Low-complexity Tracking Algorithm for Surveillance in IoVT Using Stationary Neuromorphic Vision Sensors [article]

Jyotibdha Acharya, Andres Ussa Caycedo, Vandana Reddy Padala, Rishi Raj Sidhu Singh, Garrick Orchard, Bharath Ramesh, Arindam Basu
2019 arXiv   pre-print
In this paper, we present EBBIOT-a novel paradigm for object tracking using stationary neuromorphic vision sensors in low-power sensor nodes for the Internet of Video Things (IoVT).  ...  We exploit the motion triggering aspect of neuromorphic sensors to generate region proposals based on event density counts with >1000X less memory and computes compared to frame based approaches.  ...  CONCLUSION In this paper, we presented EBBIOT -a novel paradigm for object tracking using stationary neuromorphic vision sensors in low-power sensor nodes for IoVT applications and demonstrated reliable  ... 
arXiv:1910.01851v1 fatcat:74esgoxqd5db5l7f6saju5hr5y
« Previous Showing results 1 — 15 out of 922 results