Journal ArticleDOI
Obstacle detection with a Photonic Mixing Device-camera in autonomous vehicles
Reads0
Chats0
TLDR
A collision avoidance system, based on a modern Time-Of-Flight camera, which is capable of all kinds of objects, including pedestrians as well as bicycles or vehicles, and integrated into an autonomous vehicle.Abstract:
In autonomous vehicles as well as in modern driver assistance systems, obstacle detection shows to be the most important task to be achieved This paper presents a collision avoidance system, based on a modern Time-Of-Flight camera These cameras allow a 3D perception of the environment, in which obstacles can be detected, independent of special features Thus, the system is capable of all kinds of objects, including pedestrians as well as bicycles or vehicles The used Photonic Mixing Device (PMD) camera has a measurement range of up to 50 m The system is integrated into an autonomous vehicle, on which detected obstacles are investigated in detail The vehicle steering commands are then generated by a behaviour network, depending on the presence of obstacles in the driving laneread more
Citations
More filters
Proceedings ArticleDOI
Capturing Time-of-Flight data with confidence
TL;DR: This paper proposes an improved per-pixel confidence measure using a Random Forest regressor trained with real-world data and argues that an improved confidence measure leads to superior reconstructions in subsequent steps of traditional scan processing pipelines.
Proceedings ArticleDOI
Joint self-localization and tracking of generic objects in 3D range data
Frank Moosmann,Christoph Stiller +1 more
TL;DR: A new algorithm is proposed that treats both the estimation of the trajectory of a sensor and the detection and tracking of moving objects jointly and has applicability to any type of environment since specific object models are not used at any algorithm stage.
Capturing Time-of-Flight data with confidence.
TL;DR: In this article, an improved per-pixel confidence measure using a Random Forest regressor trained with real-world data was proposed to estimate the amplitude of each time-of-flight sample.
Proceedings ArticleDOI
Motion estimation from range images in dynamic outdoor scenes
Frank Moosmann,Thierry Fraichard +1 more
TL;DR: This work proposes to first segment the range image into segments using a recently proposed segmentation criterion to derive a dense motion field based on range images only, and introduces dynamic mapping, i.e. the accumulation of measurements for moving objects.
Proceedings ArticleDOI
On-road vehicle detection during dusk and at night
TL;DR: Vehicles in front of the own car are recognized by detection of their front or rear lights, using a perspective blob filter and subsequently searching for corresponding light pairs, to distinguish the maneuver state of the vehicle.
References
More filters
Journal ArticleDOI
Seeded region growing
Richard Adams,Leanne Bischof +1 more
TL;DR: This correspondence presents a new algorithm for segmentation of intensity images which is robust, rapid, and free of tuning parameters, and suggests two ways in which it can be employed, namely, by using manual seed selection or by automated procedures.
BookDOI
An Introduction to the Kalman Filter
Greg Welch,Gary Bishop +1 more
TL;DR: The discrete Kalman filter as mentioned in this paper is a set of mathematical equations that provides an efficient computational (recursive) means to estimate the state of a process, in a way that minimizes the mean of the squared error.