AER Building Blocks for Multi-Layer Multi-Chip Neuromorphic Vision Systems

A 5-layer neuromorphic vision processor whose components communicate spike events asychronously using the address-eventrepresentation (AER) is demonstrated. The system includes a retina chip, two convolution chips, a 2D winner-take-all chip, a delay line chip, a learning classifier chip, and a set of PCBs for computer interfacing and address space remappings. The components use a mixture of analog and digital computation and will learn to classify trajectories of a moving object. A complete experimental setup and measurements results are shown.Unión Europea IST-2001-34124 (CAVIAR)Ministerio de Ciencia y Tecnología TIC-2003-08164-C0

Asynchronous Corner Tracking Algorithm based on Lifetime of Events for DAVIS Cameras

Event cameras, i.e., the Dynamic and Active-pixel Vision Sensor (DAVIS) ones, capture the intensity changes in the scene and generates a stream of events in an asynchronous fashion. The output rate of such cameras can reach up to 10 million events per second in high dynamic environments. DAVIS cameras use novel vision sensors that mimic human eyes. Their attractive attributes, such as high output rate, High Dynamic Range (HDR), and high pixel bandwidth, make them an ideal solution for applications that require high-frequency tracking. Moreover, applications that operate in challenging lighting scenarios can exploit the high HDR of event cameras, i.e., 140 dB compared to 60 dB of traditional cameras. In this paper, a novel asynchronous corner tracking method is proposed that uses both events and intensity images captured by a DAVIS camera. The Harris algorithm is used to extract features, i.e., frame-corners from keyframes, i.e., intensity images. Afterward, a matching algorithm is used to extract event-corners from the stream of events. Events are solely used to perform asynchronous tracking until the next keyframe is captured. Neighboring events, within a window size of 5x5 pixels around the event-corner, are used to calculate the velocity and direction of extracted event-corners by fitting the 2D planar using a randomized Hough transform algorithm. Experimental evaluation showed that our approach is able to update the location of the extracted corners up to 100 times during the blind time of traditional cameras, i.e., between two consecutive intensity images.Comment: Accepted to 15th International Symposium on Visual Computing (ISVC2020

Asynchronous, Photometric Feature Tracking using Events and Frames

We present a method that leverages the complementarity of event cameras and standard cameras to track visual features with low-latency. Event cameras are novel sensors that output pixel-level brightness changes, called "events". They offer significant advantages over standard cameras, namely a very high dynamic range, no motion blur, and a latency in the order of microseconds. However, because the same scene pattern can produce different events depending on the motion direction, establishing event correspondences across time is challenging. By contrast, standard cameras provide intensity measurements (frames) that do not depend on motion direction. Our method extracts features on frames and subsequently tracks them asynchronously using events, thereby exploiting the best of both types of data: the frames provide a photometric representation that does not depend on motion direction and the events provide low-latency updates. In contrast to previous works, which are based on heuristics, this is the first principled method that uses raw intensity measurements directly, based on a generative event model within a maximum-likelihood framework. As a result, our method produces feature tracks that are both more accurate (subpixel accuracy) and longer than the state of the art, across a wide variety of scenes.Comment: 22 pages, 15 figures, Video: https://youtu.be/A7UfeUnG6c

Semi-Dense 3D Reconstruction with a Stereo Event Camera

Event cameras are bio-inspired sensors that offer several advantages, such as low latency, high-speed and high dynamic range, to tackle challenging scenarios in computer vision. This paper presents a solution to the problem of 3D reconstruction from data captured by a stereo event-camera rig moving in a static scene, such as in the context of stereo Simultaneous Localization and Mapping. The proposed method consists of the optimization of an energy function designed to exploit small-baseline spatio-temporal consistency of events triggered across both stereo image planes. To improve the density of the reconstruction and to reduce the uncertainty of the estimation, a probabilistic depth-fusion strategy is also developed. The resulting method has no special requirements on either the motion of the stereo event-camera rig or on prior knowledge about the scene. Experiments demonstrate our method can deal with both texture-rich scenes as well as sparse scenes, outperforming state-of-the-art stereo methods based on event data image representations.Comment: 19 pages, 8 figures, Video: https://youtu.be/Qrnpj2FD1e

Self or other: Directors’ attitudes towards policy initiatives for external board evaluation

Recurrent crises in corporate governance have board practice and created policy pressure to assess the effectiveness of boards. Since the 1990s boards have faced calls to undertake regular, formal evaluation. Since 2010, the UK Corporate Governance Code has urged large corporations to engage outside parties to conduct them at least every three years, a move that other jurisdictions have copied. Despite this policy importance, little research has been conducted into processes or outcomes of board evaluation. This study explores the attitudes of directors on evaluation, whether self-administered or facilitated by others. We find acceptance of the principle but reservations about the value and even honesty in questionnaire-based approaches. We find scepticism about, but also acknowledgement of, the benefits of using outside facilitators, especially for their objectivity and because their interviewing elicits insights into board dynamics. As this practice expands beyond listed companies to non-listed ones, charities, and even governance branches of government, our findings point to a need to professionalise outside facilitation

Induction by agrin of ectopic postsynaptic-like membrane in innervated muscle

Two factors secreted from the nerve terminal, agrin and neuregulin, have been postulated to induce localization of the acetylcholine receptors (AChRs) to the subsynaptic membrane in skeletal muscle fibers. The principal function ascribed to neuregulin is induction of AChR subunit gene expression and to agrin is the aggregation of AChRs. Here we report that when myoblasts engineered to secrete an agrin fragment were placed into the nerve-free region of denervated rodent muscle, the host muscle fibers expressed AChR ɛ-subunit gene transcripts, characteristic of the neuromuscular synapse in adult muscle. Transcripts were colocalized with agrin deposits and AChR clusters that were resistant to electrical muscle activity. More directly, single innervated muscle fibers injected intracellularly with agrin expression plasmids in their extrasynaptic region developed a functional ectopic postsynaptic membrane with clusters of adult-type AChR channels and acetylcholinesterase and accumulation of myonuclei. The results demonstrate that agrin is the principal neural signal that induces the formation of the subsynaptic apparatus in the muscle fiber and controls locally, either indirectly or directly, the transcription of AChR subunit genes and the aggregation of AChRs