Long-Lived Accurate Keypoints in Event Streams

We present a novel end-to-end approach to keypoint detection and tracking in an event stream that provides better precision and much longer keypoint tracks than previous methods. This is made possible by two contributions working together. First, we propose a simple procedure to generate stable keypoint labels, which we use to train a recurrent architecture. This training data results in detections that are very consistent over time. Moreover, we observe that previous methods for keypoint detection work on a representation (such as the time surface) that integrates events over a period of time. Since this integration is required, we claim it is better to predict the keypoints' trajectories for the time period rather than single locations, as done in previous approaches. We predict these trajectories in the form of a series of heatmaps for the integration time period. This improves the keypoint localization. Our architecture can also be kept very simple, which results in very fast inference times. We demonstrate our approach on the HVGA ATIS Corner dataset as well as "The Event-Camera Dataset and Simulator" dataset, and show it results in keypoint tracks that are three times longer and nearly twice as accurate as the best previous state-of-the-art methods. We believe our approach can be generalized to other event-based camera problems, and we release our source code to encourage other authors to explore it

End-to-End Driving in a Realistic Racing Game with Deep Reinforcement Learning

International audienc

FIREBall-2: advancing TRL while doing proof-of-concept astrophysics on a suborbital platform

Here we discuss advances in UV technology over the last decade, with an emphasis on photon counting, low noise, high efficiency detectors in sub-orbital programs. We focus on the use of innovative UV detectors in a NASA astrophysics balloon telescope, FIREBall-2, which successfully flew in the Fall of 2018. The FIREBall-2 telescope is designed to make observations of distant galaxies to understand more about how they evolve by looking for diffuse hydrogen in the galactic halo. The payload utilizes a 1.0-meter class telescope with an ultraviolet multi-object spectrograph and is a joint collaboration between Caltech, JPL, LAM, CNES, Columbia, the University of Arizona, and NASA. The improved detector technology that was tested on FIREBall-2 can be applied to any UV mission. We discuss the results of the flight and detector performance. We will also discuss the utility of sub-orbital platforms (both balloon payloads and rockets) for testing new technologies and proof-of-concept scientific ideasComment: Submitted to the Proceedings of SPIE, Defense + Commercial Sensing (SI19

La région de Rouen - Détermination – Délimitation

Matha J., Perot Paul-Etienne. La région de Rouen - Détermination – Délimitation. In: Études Normandes, livraison 8, n°24, 3e trimestre 1953. La région de Rouen - Détermination – Délimitation. pp. 461-484

L’agglomération Rouennaise. Détermination. Délimitation

Perot Paul-Etienne, Plantrou Pierre. L’agglomération Rouennaise. Détermination. Délimitation. In: Études Normandes, livraison 1, n°3, 4e trimestre 1951. L’agglomération rouennaise. pp. 1-16

Dynamic Incorporation of Foreign Law

Lawmaking bodies in one polity sometimes incorporate the law of another polity “dynamically,” so that when the law of the foreign jurisdiction changes, the law of the incorporating jurisdiction changes automatically. Dynamic incorporation can save lawmaking costs, lead to better legal rules and standards, and solve collective action problems. Thus, the phenomenon is widespread. However, dynamic incorporation delegates lawmaking power. Further, as the formal and practical barriers to revocation of the act of dynamic incorporation become higher, that act comes closer to a cession of sovereignty, and for democratic polities, such sessions entail a democratic loss. Accordingly, dynamic incorporation of foreign law has proven controversial both within federal systems and at the international level. The problem is most acute when nation-states agree to delegate lawmaking power to a supra-national entity. In order to gain the reciprocal benefits of cooperation and coordination, the delegation must be functionally irrevocable or nearly so. Representation of the member nation-states within the decision-making structures of the supra-national entity can ameliorate but cannot fully compensate for the resulting democracy losses suffered by those nation-states. More broadly, the benefits of dynamic incorporation must always be balanced against its costs, including the cost to self-governance

Detecting Stable Keypoints from Events through Image Gradient Prediction

International audienceWe present a method that detects stable keypoints from an event stream at high speed with a low memory footprint. Our key observation connects two points: It should be easier to reconstruct the image gradients rather than the image itself from the events, and the Harris corner detector, one of the most reliable keypoint detectors for short baseline regular images, depends on the image gradients, not the image. We therefore introduce a recurrent convolutional neural network to predict image gradients from events. As image gradients and events are correlated, this prediction task is relatively easy and we can keep this network very small. We train our network solely on synthetic data. Extracting Harris corners from these gradients is then very efficient. Moreover, in contrast to learned methods, we can change the hyperparameters of the detector without retraining. Our experiments confirm that predicting image gradients rather than images is much more efficient, and that our approach predicts stable corner points which are easier to track for a longer time compared to state-of-the-art event-based methods