Open AccessJournal Article
Model Based Tracking on 3D Objects
TL;DR: A new tracking algorithm, based on local minimum energy, is proposed for matching between a projected model and corresponding image features in real-time in order to track rigid objects with known geometric features in 6 degrees of freedom arbitrary motion.
read more
Abstract: In this paper, a new tracking algorithm, based on local minimum energy, is proposed for matching between a projected model and corresponding image features in real-time. The algorithm is simple and accurate comparing with known literature. It has added advantage of robustness to changes in lighting or background and requires only a workstation with a frame grabber card installed. By using the proposed algorithm, a real-time motion tracking is performed. In practice, rigid objects with known geometric features are to be tracked in 6 degrees of freedom arbitrary motion.
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
Real-Time 3D Motion Tracking with Known Geometric Models
TL;DR: A new invariance-based method to eliminate false matches caused by strong shadow or occlusion and a linear least squares method and the orthonormal rotation matrix are used for motion estimation and pose update of the six degrees of freedom.
49
References
A Computational Approach to Edge Detection
TL;DR: There is a natural uncertainty principle between detection and localization performance, which are the two main goals, and with this principle a single operator shape is derived which is optimal at any scale.
29.9K
Snakes : Active Contour Models
TL;DR: This work uses snakes for interactive interpretation, in which user-imposed constraint forces guide the snake near features of interest, and uses scale-space continuation to enlarge the capture region surrounding a feature.
Model-Based Object Tracking in Traffic Scenes
Dieter Koller,Konstantinos Daniilidis,T. Thórhallson,Hans-Hellmut Nagel,Hans-Hellmut Nagel +4 more
- 19 May 1992
TL;DR: This contribution addresses the problem of detection and tracking of moving vehicles in image sequences from traffic scenes recorded by a stationary camera by using a parameterized vehicle model and a recursive estimator based on a motion model for motion estimation.
On the detection of motion and the computation of optical flow
James H. Duncan,T.-C. Chou +1 more
TL;DR: It is shown that the spatial and temporal derivatives of this function can be used to compute the component of the optical flow that is normal to the zero-crossing contours, and is insensitive to nonconvective temporal and spatial variations in the image intensity.
104