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Your search keyword '"Bamford, Simeon"' showing total 19 results
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19 results on '"Bamford, Simeon"'

1. LuvHarris: A Practical Corner Detector for Event-cameras

Author

Glover, Arren, Dinale, Aiko, Rosa, Leandro De Souza, Bamford, Simeon, and Bartolozzi, Chiara

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

There have been a number of corner detection methods proposed for event cameras in the last years, since event-driven computer vision has become more accessible. Current state-of-the-art have either unsatisfactory accuracy or real-time performance when considered for practical use, for example when a camera is randomly moved in an unconstrained environment. In this paper, we present yet another method to perform corner detection, dubbed look-up event-Harris (luvHarris), that employs the Harris algorithm for high accuracy but manages an improved event throughput. Our method has two major contributions, 1. a novel "threshold ordinal event-surface" that removes certain tuning parameters and is well suited for Harris operations, and 2. an implementation of the Harris algorithm such that the computational load per event is minimised and computational heavy convolutions are performed only "as-fast-as-possible", i.e. only as computational resources are available. The result is a practical, real-time, and robust corner detector that runs more than 2.6x the speed of current state-of-the-art; a necessity when using high-resolution event-camera in real-time. We explain the considerations taken for the approach, compare the algorithm to current state-of-the-art in terms of computational performance and detection accuracy, and discuss the validity of the proposed approach for event cameras.

Published
2021

3. Synaptic rewiring in neuromorphic VLSI for topographic map formation

Author

Bamford, Simeon A., Willshaw, David., and Murray, Alan

Subjects
621.3, synaptic rewiring, neuromorphic VLSI, topographic map formation, very large scale integration
Abstract

A generalised model of biological topographic map development is presented which combines both weight plasticity and the formation and elimination of synapses (synaptic rewiring) as well as both activity-dependent and -independent processes. The question of whether an activity-dependent process can refine a mapping created by an activity-independent process is investigated using a statistical approach to analysingmapping quality. The model is then implemented in custom mixed-signal VLSI. Novel aspects of this implementation include: (1) a distributed and locally reprogrammable address-event receiver, with which large axonal fan-out does not reduce channel capacity; (2) an analogue current-mode circuit for Euclidean distance calculation which is suitable for operation across multiple chips; (3) slow probabilistic synaptic rewiring driven by (pseudo-)random noise; (4) the application of a very-low-current design technique to improving the stability of weights stored on capacitors; (5) exploiting transistor non-ideality to implement partially weightdependent spike-timing-dependent plasticity; (6) the use of the non-linear capacitance of MOSCAP devices to compensate for other non-linearities. The performance of the chip is characterised and it is shown that the fabricated chips are capable of implementing the model, resulting in biologically relevant behaviours such as activity-dependent reduction of the spatial variance of receptive fields. Complementing a fast synaptic weight change mechanism with a slow synapse rewiring mechanism is suggested as a method of increasing the stability of learned patterns.

Published
2009

7. Synaptic Rewiring for Topographic Map Formation

Author

Bamford, Simeon A., Murray, Alan F., Willshaw, David J., Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Kůrková, Véra, editor, Neruda, Roman, editor, and Koutník, Jan, editor

Published
2008
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14. Event-Based Tone Mapping for Asynchronous Time-Based Image Sensor.

Author

Chane, Camille Simon, Sio-Hoi Ieng, Posch, Christoph, Benosman, Ryad B., Bamford, Simeon A., and Martel, Julien N. P.

Subjects
IMAGE sensors, TONE (Phonetics)
Abstract

The asynchronous time-based neuromorphic image sensor ATIS is an array of autonomously operating pixels able to encode luminance information with an exceptionally high dynamic range (>143 dB). This paper introduces an event-based methodology to display data from this type of event-based imagers, taking into account the large dynamic range and high temporal accuracy that go beyond available mainstream display technologies. We introduce an event-based tone mapping methodology for asynchronously acquired time encoded gray-level data. A global and a local tone mapping operator are proposed. Both are designed to operate on a stream of incoming events rather than on time frame windows. Experimental results on real outdoor scenes are presented to evaluate the performance of the tone mapping operators in terms of quality, temporal stability, adaptation capability, and computational time. [ABSTRACT FROM AUTHOR]

Published
2016
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19. Large Developing Receptive Fields Using a Distributed and Locally Reprogrammable Address-Event Receiver.

Author

Bamford, Simeon A., Murray, Alan F., and Willshaw, David J.

Subjects
*EUCLIDEAN algorithm, *SYNAPSES, *TOPOGRAPHIC maps, *ELECTRIC network topology, *NERVE endings
Abstract

A distributed and locally reprogrammable address--event receiver has been designed, in which incoming address--events are monitored simultaneously by all synapses, allowing for arbitrarily large axonal fan-out without reducing channel capacity. Synapses can change the address of their presynaptic neuron, allowing the distributed implementation of a biologically realistic learning rule, with both synapse formation and elimination (synaptic rewiring). Probabilistic synapse formation leads to topographic map development, made possible by a cross-chip current-mode calculation of Euclidean distance. As well as synaptic plasticity in rewiring, synapses change weights using a competitive Hebbian learning rule (spike-timing-dependent plasticity). The weight plasticity allows receptive fields to be modified based on spatio-temporal correlations in the inputs, and the rewiring plasticity allows these modifications to become embedded in the network topology. [ABSTRACT FROM AUTHOR]

Published
2010
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