114 research outputs found
Event-based Face Detection and Tracking in the Blink of an Eye
We present the first purely event-based method for face detection using the
high temporal resolution of an event-based camera. We will rely on a new
feature that has never been used for such a task that relies on detecting eye
blinks. Eye blinks are a unique natural dynamic signature of human faces that
is captured well by event-based sensors that rely on relative changes of
luminance. Although an eye blink can be captured with conventional cameras, we
will show that the dynamics of eye blinks combined with the fact that two eyes
act simultaneously allows to derive a robust methodology for face detection at
a low computational cost and high temporal resolution. We show that eye blinks
have a unique temporal signature over time that can be easily detected by
correlating the acquired local activity with a generic temporal model of eye
blinks that has been generated from a wide population of users. We furthermore
show that once the face is reliably detected it is possible to apply a
probabilistic framework to track the spatial position of a face for each
incoming event while updating the position of trackers. Results are shown for
several indoor and outdoor experiments. We will also release an annotated data
set that can be used for future work on the topic
Détermination de la géométrie épipolaire d'images panoramiques cylindriques
- Nous présentons ici la géométrie d'un capteur panoramique tournant, ainsi que la généralisation du concept de contrainte épipolaire sur des images de type cylindrique. Différents procédés de minimisation sont utilisés pour retrouver certains paramètres expérimentaux. Cette contrainte permet ainsi d'optimiser de l'étape de recherche de points appariés afin de reconstituer la configuration tridimensionnelle de la scène observée à partir d'images cylindriques haute définition
Neutron-Induced, Single-Event Effects on Neuromorphic Event-based Vision Sensor: A First Step Towards Space Applications
This paper studies the suitability of neuromorphic event-based vision cameras
for spaceflight, and the effects of neutron radiation on their performance.
Neuromorphic event-based vision cameras are novel sensors that implement
asynchronous, clockless data acquisition, providing information about the
change in illuminance greater than 120dB with sub-millisecond temporal
precision. These sensors have huge potential for space applications as they
provide an extremely sparse representation of visual dynamics while removing
redundant information, thereby conforming to low-resource requirements. An
event-based sensor was irradiated under wide-spectrum neutrons at Los Alamos
Neutron Science Center and its effects were classified. We found that the
sensor had very fast recovery during radiation, showing high correlation of
noise event bursts with respect to source macro-pulses. No significant
differences were observed between the number of events induced at different
angles of incidence but significant differences were found in the spatial
structure of noise events at different angles. The results show that
event-based cameras are capable of functioning in a space-like, radiative
environment with a signal-to-noise ratio of 3.355. They also show that
radiation-induced noise does not affect event-level computation. We also
introduce the Event-based Radiation-Induced Noise Simulation Environment
(Event-RINSE), a simulation environment based on the noise-modelling we
conducted and capable of injecting the effects of radiation-induced noise from
the collected data to any stream of events in order to ensure that developed
code can operate in a radiative environment. To the best of our knowledge, this
is the first time such analysis of neutron-induced noise analysis has been
performed on a neuromorphic vision sensor, and this study shows the advantage
of using such sensors for space applications
Improved Contrast Sensitivity DVS and its Application to Event-Driven Stereo Vision
This paper presents a new DVS sensor with
one order of magnitude improved contrast sensitivity over
previous reported DVSs. This sensor has been applied to a
bio-inspired event-based binocular system that performs
3D event-driven reconstruction of a scene. Events from two
DVS sensors are matched by using precise timing
information of their ocurrence. To improve matching
reliability, satisfaction of epipolar geometry constraint is
required, and simultaneously available information on the
orientation is used as an additional matching constraint.Ministerio de Economía y Competitividad PRI-PIMCHI-2011-0768Ministerio de Economía y Competitividad TEC2009-10639-C04-01Junta de Andalucía TIC-609
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