An Approach to Distance Estimation with Stereo Vision Using Address-Event-Representation

Domínguez-Morales, Manuel; Jiménez-Fernández, Ángel; Paz, Rafael; López-Torres, M. R.; Cerezuela-Escudero, Elena; Linares-Barranco, A.; Jiménez-Moreno, Gabriel; Morgado, Arturo

doi:10.1007/978-3-642-24955-6_23

Cited by 8 publications

(6 citation statements)

References 11 publications

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“…To do that, a new Multi-Hold&Fire (MH&F) was implemented for this work, which was tested in previous works [22]. Its functionality is based on the H&F module but, in this case, it is extended to a 128 × 128 matrix, storing the subtraction data for each pixel (see Figure 4).…”

Section: Global Disparity Calculationmentioning

confidence: 99%

Neuronal Specialization for Fine-Grained Distance Estimation Using a Real-Time Bio-Inspired Stereo Vision System

Domínguez-Morales

Ríos-Navarro

et al. 2019

Electronics

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The human binocular system performs very complex operations in real-time tasks thanks to neuronal specialization and several specialized processing layers. For a classic computer vision system, being able to perform the same operation requires high computational costs that, in many cases, causes it to not work in real time: this is the case regarding distance estimation. This work details the functionality of the biological processing system, as well as the neuromorphic engineering research branch—the main purpose of which is to mimic neuronal processing. A distance estimation system based on the calculation of the binocular disparities with specialized neuron populations is developed. This system is characterized by several tests and executed in a real-time environment. The response of the system proves the similarity between it and human binocular processing. Further, the results show that the implemented system can work in a real-time environment, with a distance estimation error of 15% (8% for the characterization tests).

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Section: Global Disparity Calculationmentioning

confidence: 99%

Neuronal Specialization for Fine-Grained Distance Estimation Using a Real-Time Bio-Inspired Stereo Vision System

Domínguez-Morales

Ríos-Navarro

et al. 2019

Electronics

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“…There are multiple noise filtering methods for event-based data available in the literature and the Nearest Neighbor (NNb) filter (Dominguez-Morales, 2011 ; Ieng et al, 2014 ; Linares-Barranco et al, 2015 ; Liu et al, 2015 ) is the most commonly employed filtering method among the other approaches like differing polarity, refractory period and inter-spike interval (Czech and Orchard, 2016 ). Because the focus of our task is to extract the moving objects and remove the background activity, we look at the NNb filter, which captures the activity of the moving object more aptly.…”

Section: Noise Filtering Approach In Software and On Truenorthmentioning

confidence: 99%

“…In this work, we focus on the case of a static camera observing a scene such as in a surveillance scenario. Noise filtering algorithms such as nearest neighbor for event-based imagers presented in the literature exploit the temporal correlation associated with activity across the neighborhood pixels (Dominguez-Morales, 2011 ; Ieng et al, 2014 ; Linares-Barranco et al, 2015 ; Liu et al, 2015 ; Czech and Orchard, 2016 ). Though these filters capture the activity of the fast moving objects, they typically filter out the activity by the small and slow-moving objects due to weak temporal support.…”

Section: Introductionmentioning

confidence: 99%

A Noise Filtering Algorithm for Event-Based Asynchronous Change Detection Image Sensors on TrueNorth and Its Implementation on TrueNorth

2018

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Asynchronous event-based sensors, or “silicon retinae,” are a new class of vision sensors inspired by biological vision systems. The output of these sensors often contains a significant number of noise events along with the signal. Filtering these noise events is a common preprocessing step before using the data for tasks such as tracking and classification. This paper presents a novel spiking neural network-based approach to filtering noise events from data captured by an Asynchronous Time-based Image Sensor on a neuromorphic processor, the IBM TrueNorth Neurosynaptic System. The significant contribution of this work is that it demonstrates our proposed filtering algorithm outperforms the traditional nearest neighbor noise filter in achieving higher signal to noise ratio (~10 dB higher) and retaining the events related to signal (~3X more). In addition, for our envisioned application of object tracking and classification under some parameter settings, it can also generate some of the missing events in the spatial neighborhood of the signal for all classes of moving objects in the data which are unattainable using the nearest neighbor filter.

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“…Color change detection . Combining the pixel architecture of a DVS with stacked photodiodes at different depths in standard silicon, it was possible to create an image sensor whose pixels only react to color changes (transient shifts within the spectrum). Stereo vision . The combination of two or more DVSs recording images from different localizations allows to determine distances and depth, after processing their outputs.…”

Section: Dynamic Vision Sensorsmentioning

confidence: 99%

Applications of event‐based image sensors—Review and analysis

Leñero‐Bardallo

Carmona-Galán

Rodríguez-Vázquez

2018

Circuit Theory & Apps

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The spread of event-driven asynchronous vision sensors during the last years has increased significantly the industrial interest and the application scenarios for them. This article reviews the main fields of application that event-based image sensors have found during the last 20 years. We focus in the description of applications where such devices can outperform conventional frame-based sensors. The practical functions of the three main families of asynchronous event-based sensors are analyzed. The article also studies what are the factors that increase nowadays the demand of sensors that minimize the power and bandwidth consumption. Moreover, the technological factors that have facilitated the development of asynchronous sensors are discussed.

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An Approach to Distance Estimation with Stereo Vision Using Address-Event-Representation

Cited by 8 publications

References 11 publications

Neuronal Specialization for Fine-Grained Distance Estimation Using a Real-Time Bio-Inspired Stereo Vision System

Neuronal Specialization for Fine-Grained Distance Estimation Using a Real-Time Bio-Inspired Stereo Vision System

A Noise Filtering Algorithm for Event-Based Asynchronous Change Detection Image Sensors on TrueNorth and Its Implementation on TrueNorth

Applications of event‐based image sensors—Review and analysis

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