Event Vision for Autonomous Off-Road Navigation

AlRemeithi, Hamad; Zayer, Fakhreddine; Dias, Jorge; Khonji, Majid

doi:10.1007/978-3-031-28715-2_8

Cited by 1 publication

(1 citation statement)

References 66 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Furthermore, the scope of these advancements has broad implications for industries such as autonomous vehicle navigation, robotic surgery, and augmented reality, where enhanced calibration techniques enable more precise and real-time interactions between event and CMOS cameras [24,25]. The integration of these technologies with emerging IoT devices and smart city infrastructure has also opened up transformative opportunities for urban development.…”

Section: Discussionmentioning

confidence: 99%

Real-World Spatial Synchronization of Event-CMOS Cameras through Deep Learning: A Novel CNN-DGCNN Approach

Mizrahi,

Laufer,

Zuckerman

2024

Sensors

View full text Add to dashboard Cite

This paper presents a new deep-learning architecture designed to enhance the spatial synchronization between CMOS and event cameras by harnessing their complementary characteristics. While CMOS cameras produce high-quality imagery, they struggle in rapidly changing environments—a limitation that event cameras overcome due to their superior temporal resolution and motion clarity. However, effective integration of these two technologies relies on achieving precise spatial alignment, a challenge unaddressed by current algorithms. Our architecture leverages a dynamic graph convolutional neural network (DGCNN) to process event data directly, improving synchronization accuracy. We found that synchronization precision strongly correlates with the spatial concentration and density of events, with denser distributions yielding better alignment results. Our empirical results demonstrate that areas with denser event clusters enhance calibration accuracy, with calibration errors increasing in more uniformly distributed event scenarios. This research pioneers scene-based synchronization between CMOS and event cameras, paving the way for advancements in mixed-modality visual systems. The implications are significant for applications requiring detailed visual and temporal information, setting new directions for the future of visual perception technologies.

show abstract

Section: Discussionmentioning

confidence: 99%