Publication/Creation Date

January 25 2021

Creators/Contributors

Indian Institute Of Science (IISc) (creator)
Aakash Khochare (creator)
Aravindhan Krishnan (creator)
Yogesh Simmhan (creator)

Description

Abstract:

Advances in deep neural networks (DNN) and computer vision (CV) algorithms have made it feasible to extract meaningful insights from large-scale deployments of urban cameras. Tracking an object of interest across the camera network in near real-time is a canonical problem. However, current tracking platforms have two key limitations: 1) They are monolithic, proprietary and lack the ability to rapidly incorporate sophisticated tracking models, and 2) They are less responsive to dynamism across wide-area computing resources that include edge, fog, and cloud abstractions. We address these gaps using Anveshak , a runtime platform for composing and coordinating distributed tracking applications. It provides a domain-specific dataflow programming model to intuitively compose a tracking application, supporting contemporary CV advances like query fusion and re-identification, and enabling dynamic scoping of the camera network's search space to avoid wasted computation. We also offer tunable batching and data-dropping strategies for dataflow blocks deployed on distributed resources to respond to network and compute variability. These balance the tracking accuracy, its real-time performance, and the active camera-set size. We illustrate the concise expressiveness of the programming model for four tracking applications. Our detailed experiments for a network of 1000 camera-feeds on modest resources exhibit the tunable scalability, performance, and quality trade-offs enabled by our dynamic tracking, batching, and dropping strategies.

Augments

Tracking, Watching, Surveilling

Technology Keywords

Artificial Intelligence (AI), Algorithms , Deep Learning, Computer Vision, Cameras, Surveillance Cameras, Object Tracking, Real-Time, Video Analytics, Cloud Computing, Edge Computing, Big Data, Ambient Interaction, Smart Cities, Spotlights

Keywords

Surveillance, Urban, Research

Source

https://ieeexplore.ieee.org/document/9314091