22 citations · 48 across the 11 of their papers we have counts for
11 papers
Motion Segmentation for Neuromorphic Aerial Surveillance
Sami Arja, Alexandre Marcireau, Saeed Afshar +2
Aerial surveillance demands rapid and precise detection of moving objects in dynamic environments. Event cameras, which draw inspiration from biological vision systems, present a p…
Superevents: Towards Native Semantic Segmentation for Event-based Cameras
Weng Fei Low, Ankit Sonthalia, Zhi Gao +2
Most successful computer vision models transform low-level features, such as Gabor filter responses, into richer representations of intermediate or mid-level complexity for downstr…
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…
EBBINNOT: A Hardware Efficient Hybrid Event-Frame Tracker for Stationary Dynamic Vision Sensors
Vivek Mohan, Deepak Singla, Tarun Pulluri +5
As an alternative sensing paradigm, dynamic vision sensors (DVS) have been recently explored to tackle scenarios where conventional sensors result in high data rate and processing…
HyNNA: Improved Performance for Neuromorphic Vision Sensor based Surveillance using Hybrid Neural Network Architecture
Deepak Singla, Soham Chatterjee, Lavanya Ramapantulu +3
Applications in the Internet of Video Things (IoVT) domain have very tight constraints with respect to power and area. While neuromorphic vision sensors (NVS) may offer advantages…