Zobrazeno 1 - 10
of 156
pro vyhledávání: '"Davoine, Franck"'
Despite the increasing interest in enhancing perception systems for autonomous vehicles, the online calibration between event cameras and LiDAR - two sensors pivotal in capturing comprehensive environmental information - remains unexplored. We introd
Externí odkaz:
http://arxiv.org/abs/2405.18021
Publikováno v:
BMVC 2023: 829-831
Camera-LiDAR extrinsic calibration is a critical task for multi-sensor fusion in autonomous systems, such as self-driving vehicles and mobile robots. Traditional techniques often require manual intervention or specific environments, making them labou
Externí odkaz:
http://arxiv.org/abs/2309.09855
Event cameras do not produce images, but rather a continuous flow of events, which encode changes of illumination for each pixel independently and asynchronously. While they output temporally rich information, they lack any depth information which co
Externí odkaz:
http://arxiv.org/abs/2302.14444
Recently, we have been witnesses of accidents involving autonomous vehicles and their lack of sufficient information. One way to tackle this issue is to benefit from the perception of different view points, namely cooperative perception. We propose h
Externí odkaz:
http://arxiv.org/abs/2301.01250
Event cameras capture changes of illumination in the observed scene rather than accumulating light to create images. Thus, they allow for applications under high-speed motion and complex lighting conditions, where traditional framebased sensors show
Externí odkaz:
http://arxiv.org/abs/2112.10591
Publikováno v:
Pattern Recognition, Volume 122, February 2022
Point cloud segmentation is the foundation of 3D environmental perception for modern intelligent systems. To solve this problem and image segmentation, conditional random fields (CRFs) are usually formulated as discrete models in label space to encou
Externí odkaz:
http://arxiv.org/abs/2110.06085
Dempster-Shafer Theory (DST) generalizes Bayesian probability theory, offering useful additional information, but suffers from a high computational burden. A lot of work has been done to reduce the complexity of computations used in information fusio
Externí odkaz:
http://arxiv.org/abs/2107.07359
Dempster-Shafer Theory (DST) generalizes Bayesian probability theory, offering useful additional information, but suffers from a high computational burden. A lot of work has been done to reduce the complexity of computations used in information fusio
Externí odkaz:
http://arxiv.org/abs/2107.06329
LIDAR sensors are usually used to provide autonomous vehicles with 3D representations of their environment. In ideal conditions, geometrical models could detect the road in LIDAR scans, at the cost of a manual tuning of numerical constraints, and a l
Externí odkaz:
http://arxiv.org/abs/2102.03326