In automated surveillance, one is often interested in tracking road vehicles, measuring their shape in 3D world space, and determining vehicle classification. To address these tasks simultaneously, an effective approach is the constrained alignment of a prior model of 3D vehicle shape to images. Previous 3D vehicle models are either generic but overly… (More)
In traffic surveillance applications a good prior model of vehicle shape and appearance is becoming increasingly more important for tracking, shape recovery, and recognition from video. The usefulness of 2-d vehicle models is limited to a fixed viewing direction; 3-d models are nearly always more suitable. Existing 3-d vehicle models are either generic but… (More)
Retinal clinicians and researchers make extensive use of images, and the current emphasis is on digital imaging of the retinal fundus. The goal of this paper is to introduce a system, known as retinal image vessel extraction and registration system, which provides the community of retinal clinicians, researchers, and study directors an integrated suite of… (More)
This paper presents a novel algorithm for simultaneous background appearance modeling and coarse-scale vehicle recognition in traffic surveillance applications. 3-d mesh models representing a small set of vehicle classes are used to the hypothesize image segmentations into background, shadow, and vehicle regions. The algorithm optimizes vehicle class and… (More)
We present a planarity constraint and a novel three-dimensional (3D) point reconstruction algorithm for a multiview laser range slit scanner. The constraint is based on the fact that all observed points on a projected laser line lie on the same plane of laser light in 3D. The parameters of the plane of laser light linearly parametrize a homography between a… (More)
Using inexpensive and readily available materials–a calibrated pair of cameras and a laser line projector–a 3D laser range scanner which requires no tracking is implemented in this paper. We introduce a planarity constraint for reconstruction, based on the fact that all points observed on a laser line in an image are on the same plane of laser light in 3D.… (More)
Vehicle tracking in video sequences is typically carried out by matching 2-d views (images or features) of the vehicle from one frame to the next. These views are adapted by gradual changes in 2-d image transforms between frames. This approach can work well for sequences where the vehicle projection is not highly perspective and 3-d vehicle orientation with… (More)
(a) (b) (c) (d) Figure 1: (a) One of the original images from our sequence. (b) Reconstructed 3D points from all images projected into the same image plane. (c) The depth map computed for this image. (d) Virtual objects inserted into the image with shadows and occlusion.