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Cameras are deployed at scale with the purpose of searching and tracking objects of interest (e.g., a suspected person) through the camera network on live videos. Such cross-camera analytics is data and compute intensive, whose costs grow with the number of cameras and time. We present Spatula, a cost-efficient system that enables scaling cross-camera analytics on edge compute boxes to large camera networks by leveraging the spatial and temporal cross-camera correlations. While such correlations have been used in computer vision community, Spatula uses them to drastically reduce the communication and computation costs by pruning search space of a query identity (e.g., ignoring frames not correlated with the query identity’s current position). Spatula provides the first system substrate on which cross-camera analytics applications can be built to efficiently harness the cross-camera correlations that are abundant in large camera deployments. Spatula reduces compute load by $8.3\times$ on an 8-camera dataset, and by $23\times-86\times$ on two datasets with hundreds of cameras (simulated from real vehicle/pedestrian traces). We have also implemented Spatula on a testbed of 5 AWS DeepLens cameras. 

Whispering-gallery-mode optical microresonators have found impactful applications in various areas due to their remarkable properties such as ultra-high quality factor (Q-factor), small mode volume, and strong evanescent field. Among these applications, controllable tuning of the optical Q-factor is vital for on-chip optical modulation and various opto-electronic devices. Here, we report an experimental demonstration with a hybrid structure formed by an ultra-high-Q microtoroid cavity and a graphene monolayer. Thanks to the strong interaction of the evanescent wave with the graphene, the structure allows the Q-factor to be controllably varied in the range of 3.9 × 10⁵∼ 6.2 × 10⁷by engineering optical absorption via changing the gap distance in between. At the same time, a resonant wavelength shift of 32 pm was also observed. Besides, the scheme enables us to approach the critical coupling with a coupling depth of 99.6%. As potential applications in integrated opto-electronic devices, we further use the system to realize a tunable optical filter with tunable bandwidth from 116.5 MHz to 2.2 GHz as well as an optical switch with a maximal extinction ratio of 31 dB and response time of 21 ms.

 

Authoring behavior narratives for heterogeneous multiagent virtual humans engaged in collaborative, localized, and task‐based behaviors can be challenging. Traditional behavior authoring frameworks are eitherspace‐centric, where occupancy parameters are specified;behavior‐centric, where multiagent behaviors are defined; oragent‐centric, where desires and intentions drive agents' behavior. In this paper, we propose to integrate these approaches into a unique framework to author behavior narratives that progressively satisfy time‐varying building‐level occupancy specifications, room‐level behavior distributions, and agent‐level motivations using a prioritized resource allocation system. This approach can generate progressively more complex and plausible narratives that satisfy spatial, behavioral, and social constraints. Possible applications of this system involve computer gaming and decision‐making in engineering and architectural design.