demonstration

A Demonstration of Tracking using Dynamic Neural Fields on a Programmable Vision Chip: Demo

Authors:

Julien N.P. Martel,

Yulia Sandamirskaya,

Piotr DudekAuthors Info & Claims

ICDSC '16: Proceedings of the 10th International Conference on Distributed Smart Camera

Pages 212 - 213

https://doi.org/10.1145/2967413.2974037

Published: 12 September 2016 Publication History

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Abstract

A demonstration is made of a programmable vision chip, containing an array of photosensors collocated with a processing circuitry and memory, implementing a Dynamic Neural Field (DNF) over a simple saliency map. The system detects and tracks moving objects with strong contrasts. The computation of the DNF's dynamics is performed entirely on the vision chip. The system solely outputs relevant information that has been processed on the array: the activity of the DNF and/or address-events corresponding to the coordinates of its bumps of activity.

References

[1]

S. J. Carey, D. R. W. Barr, A. Lopich, and P. Dudek. A 100'000 fps vision sensor with embedded 535 GOPS/W 256x256 SIMD processor array. In Proc. of the VLSI Circuits Symp.'13, pages C182--C183, 2013.

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[2]

J. N. P. Martel and Y. Sandamirskaya. A neuromorphic approach for tracking using dynamic neural fields on programmable vision-chip. In Proc. of the ACM/IEEE Internat. Conf. on Distributed Smart Cameras, ICDSC'16, 2016.

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[3]

G. Schöner and J. P. Spencer, editors. Dynamic Thinking: A Primer on Dynamic Field Theory. Oxford University Press, 2015.

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Liu YFan RGuo JNi HBhutta M(2023)In-Sensor Visual Perception and InferenceIntelligent Computing10.34133/icomputing.00432Online publication date: Jan-2023
https://doi.org/10.34133/icomputing.0043
de Jesus Osuna-Coutino JMartinez-Carranza J(2019)Binary-Patterns Based Floor Recognition Suitable for Urban Scenes2019 6th International Conference on Control, Decision and Information Technologies (CoDIT)10.1109/CoDIT.2019.8820296(1574-1579)Online publication date: Apr-2019
https://doi.org/10.1109/CoDIT.2019.8820296
de Jesús Osuna-Coutiño JMartinez-Carranza J(2019)A Binary Descriptor Invariant to Rotation and Robust to Noise (BIRRN) for Floor RecognitionPattern Recognition10.1007/978-3-030-21077-9_25(271-281)Online publication date: 18-May-2019
https://doi.org/10.1007/978-3-030-21077-9_25

A Demonstration of Tracking using Dynamic Neural Fields on a Programmable Vision Chip: Demo
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision tasks

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ICDSC '16: Proceedings of the 10th International Conference on Distributed Smart Camera

September 2016

242 pages

ISBN:9781450347860

DOI:10.1145/2967413

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

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Published: 12 September 2016

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ICDSC '16

ICDSC '16: 10th international conference on distributed smart camera

September 12 - 15, 2016

Paris, France

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Liu YFan RGuo JNi HBhutta M(2023)In-Sensor Visual Perception and InferenceIntelligent Computing10.34133/icomputing.00432Online publication date: Jan-2023
https://doi.org/10.34133/icomputing.0043
de Jesus Osuna-Coutino JMartinez-Carranza J(2019)Binary-Patterns Based Floor Recognition Suitable for Urban Scenes2019 6th International Conference on Control, Decision and Information Technologies (CoDIT)10.1109/CoDIT.2019.8820296(1574-1579)Online publication date: Apr-2019
https://doi.org/10.1109/CoDIT.2019.8820296
de Jesús Osuna-Coutiño JMartinez-Carranza J(2019)A Binary Descriptor Invariant to Rotation and Robust to Noise (BIRRN) for Floor RecognitionPattern Recognition10.1007/978-3-030-21077-9_25(271-281)Online publication date: 18-May-2019
https://doi.org/10.1007/978-3-030-21077-9_25

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A Neuromorphic Approach for Tracking using Dynamic Neural Fields on a Programmable Vision-chip

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A Neuromorphic Approach for Tracking using Dynamic Neural Fields on a Programmable Vision-chip

Randomly Spiking Dynamic Neural Fields

Hand-Eye Camera Calibration with an Optical Tracking System

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