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Found 6 papers, 2 papers with code
e-TLD: Event-based Framework for Dynamic Object Tracking
On the other hand, when the object re-enters the field-of-view of the camera, a data-driven, global sliding window detector locates the object for subsequent tracking.
A Hybrid Neuromorphic Object Tracking and Classification Framework for Real-time Systems
Deep learning inference that needs to largely take place on the 'edge' is a highly computational and memory intensive workload, making it intractable for low-power, embedded platforms such as mobile nodes and remote security applications.
EBBINNOT: A Hardware Efficient Hybrid Event-Frame Tracker for Stationary Dynamic Vision Sensors
To the best of our knowledge, this is the first time a stationary DVS based traffic monitoring solution is extensively compared to simultaneously recorded RGB frame-based methods while showing tremendous promise by outperforming state-of-the-art deep learning solutions.
HyNNA: Improved Performance for Neuromorphic Vision Sensor based Surveillance using Hybrid Neural Network Architecture
Applications in the Internet of Video Things (IoVT) domain have very tight constraints with respect to power and area.
A low-power end-to-end hybrid neuromorphic framework for surveillance applications
With the success of deep learning, object recognition systems that can be deployed for real-world applications are becoming commonplace.
PCA-RECT: An Energy-efficient Object Detection Approach for Event Cameras
We present the first purely event-based, energy-efficient approach for object detection and categorization using an event camera.
