Search Results for author:
Found 10 papers, 7 papers with code
Robust Self-calibration of Focal Lengths from the Fundamental Matrix
In this paper, we therefore propose an efficient and robust iterative method to estimate the focal lengths along with the principal points of the cameras given a fundamental matrix and priors for the estimated camera parameters.
Traffic Camera Calibration via Vehicle Vanishing Point Detection
From the detected pairs of vanishing points for multiple vehicles in a scene we establish the scene geometry by estimating the focal length of the camera and the orientation of the road plane.
Detection of 3D Bounding Boxes of Vehicles Using Perspective Transformation for Accurate Speed Measurement
We present an improved version of our algorithm for detection of 3D bounding boxes of vehicles, their tracking and subsequent speed estimation.
Ranked #1 on
Vehicle Speed Estimation
on BrnoCompSpeed
Perspective transformation for accurate detection of 3D bounding boxes of vehicles in traffic surveillance
Detection and tracking of vehicles captured by traffic surveillance cameras is a key component of intelligent traffic systems.
Ranked #2 on
Vehicle Speed Estimation
on BrnoCompSpeed
Towards Deep Learning-based 6D Bin Pose Estimation in 3D Scans
This paper focuses on a specific task of 6D pose estimation of a bin in 3D scans.
Ranked #1 on
6D Pose Estimation
on 3D-BSLS-6D
Supersampling of Data from Structured-light Scanner with Deep Learning
This paper focuses on increasing the resolution of depth maps obtained from 3D cameras using structured light technology.
Processing and Segmentation of Human Teeth from 2D Images using Weakly Supervised Learning
We introduce the TriDental dataset, consisting of 3000 oral cavity images annotated with teeth keypoints, to train a teeth keypoint detection network.
Evaluating the Significance of Outdoor Advertising from Driver's Perspective Using Computer Vision
Outdoor advertising, such as roadside billboards, plays a significant role in marketing campaigns but can also be a distraction for drivers, potentially leading to accidents.
Enhancement of 3D Camera Synthetic Training Data with Noise Models
The goal of this paper is to assess the impact of noise in 3D camera-captured data by modeling the noise of the imaging process and applying it on synthetic training data.
