Sio-Hoi Ieng

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This paper introduces a new methodology to compute dense visual flow using the precise timings of spikes from an asynchronous event-based retina. Biological retinas, and their artificial counterparts, are totally asynchronous and data-driven and rely on a paradigm of light acquisition radically different from most of the currently used frame-grabber(More)
This paper introduces a process to compute optical flow using an asynchronous event-based retina at high speed and low computational load. A new generation of artificial vision sensors has now started to rely on biologically inspired designs for light acquisition. Biological retinas, and their artificial counterparts, are totally asynchronous and data(More)
Hanme Kim1 hanme.kim@imperial.ac.uk Ankur Handa2 ah781@cam.ac.uk Ryad Benosman3 ryad.benosman@upmc.fr Sio-Hoi Ieng3 sio-hoi.ieng@upmc.fr Andrew J. Davison1 a.davison@imperial.ac.uk 1 Department of Computing, Imperial College London, London, UK 2 Department of Engineering, University of Cambridge, Cambridge, UK 3 INSERM, U968, Paris, F-75012, France;(More)
We present a novel event-based stereo matching algorithm that exploits the asynchronous visual events from a pair of silicon retinas. Unlike conventional frame-based cameras, recent artificial retinas transmit their outputs as a continuous stream of asynchronous temporal events, in a manner similar to the output cells of the biological retina. Our algorithm(More)
Epipolar geometry, the cornerstone of perspective stereo vision, has been studied extensively since the advent of computer vision. Establishing such a geometric constraint is of primary importance, as it allows the recovery of the 3-D structure of scenes. Estimating the epipolar constraints of nonperspective stereo is difficult, they can no longer be(More)
This paper presents a number of new methods for visual tracking using the output of an event-based asynchronous neuromorphic dynamic vision sensor. It allows the tracking of multiple visual features in real time, achieving an update rate of several hundred kilohertz on a standard desktop PC. The approach has been specially adapted to take advantage of the(More)
The human perception of the external world appears as a natural, immediate and effortless task. It is achieved through a number of “low-level” sensory-motor processes that provide a high-level representation adapted to complex reasoning and decision. Compared to these representations, mobile robots usually provide only low-level obstacle maps(More)
This letter presents a novel computationally efficient and robust pattern tracking method based on a time-encoded, frame-free visual data. Recent interdisciplinary developments, combining inputs from engineering and biology, have yielded a novel type of camera that encodes visual information into a continuous stream of asynchronous, temporal events. These(More)
Reliable and fast sensing of the environment is a fundamental requirement for autonomous mobile robotic platforms. Unfortunately, the frame-based acquisition paradigm at the basis of main stream artificial perceptive systems is limited by low temporal dynamics and redundant data flow, leading to high computational costs. Hence, conventional sensing and(More)
Objective. Accurate modeling of retinal information processing remains a major challenge in retinal physiology with applications in visual rehabilitation and prosthetics. Most of the current artificial retinas are fed with static frame-based information, losing thereby the fundamental asynchronous features of biological vision. The objective of this work is(More)