13 citations · 25 across the 4 of their papers we have counts for
4 papers · 1 filter
e-TLD: Event-based Framework for Dynamic Object Tracking
Bharath Ramesh, Shihao Zhang, Hong Yang +4
This paper presents a long-term object tracking framework with a moving event camera under general tracking conditions. A first of its kind for these revolutionary cameras, the tra…
A Hybrid Neuromorphic Object Tracking and Classification Framework for Real-time Systems
Andres Ussa, Chockalingam Senthil Rajen, Deepak Singla +4
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 platfo…
A low-power end-to-end hybrid neuromorphic framework for surveillance applications
Andres Ussa, Luca Della Vedova, Vandana Reddy Padala +6
With the success of deep learning, object recognition systems that can be deployed for real-world applications are becoming commonplace. However, inference that needs to largely ta…
PCA-RECT: An Energy-efficient Object Detection Approach for Event Cameras
Bharath Ramesh, Andres Ussa, Luca Della Vedova +2
We present the first purely event-based, energy-efficient approach for object detection and categorization using an event camera. Compared to traditional frame-based cameras, choos…