Learn More
This paper deals with detection and recognition of matrix codes, such as the QR codes, in high-resolution images of real-world scenes. The goal is to provide a detector capable of operation in real time even on high-resolution images (several megapixels). We present an efficient algorithm for detection of possible occurrences of the codes. This algorithm is(More)
The traditional approach in detecting sets of concurrent and/or parallel lines is to first detect lines in the image and then find such groups of them which meet the concurrence condition. The Hough Transform can be used for detecting the lines and variants of HT such as the Cascaded Hough Transform can be used to detect the vanishing points. However, these(More)
PClines is a parameterization of lines usable for efficient line detection based on the Hough transform. The talk will describe the information from CVPR2011 paper with the same name and it will extend it with more context from an upcoming Springer book "Real-Time Detection of Lines and Grids By PClines and Other Approaches". PClines is usable for real-time(More)
Figure 1: We automatically determine 3 orthogonal vanishing points, construct vehicle bounding boxes (left), and automatically determine the camera scale by knowing the statistics of vehicle dimensions. This allows us to measure dimensions and speed (right) and analyze the traffic scene. This paper proposes a method for fully automatic calibration of(More)
We introduce here an improved design of the Uniform Marker Fields and an algorithm for their fast and reliable detection. Our concept of the marker field is designed so that it can be detected and recognized for camera pose estimation: in various lighting conditions, under a severe perspective, while heavily occluded, and under a strong motion blur. Our(More)
This paper deals with automatic calibration of roadside surveillance cameras. We focus on parameters necessary for measurements in traffic-surveillance applications. Contrary to the existing solutions, our approach requires no a priori knowledge, and it works with a very wide variety of road settings (number of lanes, occlusion, quality of ground marking),(More)
(a) Input image (b) Extracted edges Figure 1: Detection of orthogonal vanishing points. Input image and ed-glets corresponding to edge points. This paper deals with the detection of orthogonal vanishing points in the Manhattan world. We are using a modified scheme of the Cascaded Hough Transform where only one Hough space is accumulated – the space of the(More)