Work

Fast Visual Feature Selection and Tracking in a Hybrid Reconfigurable Architecture

Year: 2004

Type: article

Abstract: We present a fast visual feature tracking system which takes advantage of dedicated hardware to perform the computationally intensive step of selection. A software system uses the output of the hardware selector to develop tracks using filtering and data association techniques, and image-based validation. By using separate, custom hardware to select hundreds of points per frame then associating these points to tracks in software, we achieve greater than 60Hz real-time tracking.

Source: eScholarship (California Digital Library)

Authors: Alessandro Bissacco, Jason Meltzer, Soheil Ghiasi, Stefano Soatto

Institutions: University of California, Los Angeles, University of California, Davis

Language: English

Topic: Video Surveillance and Tracking Methods

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funder: Ministry of Education, India

OpenAlex ID: W209228566

FWCI: 0.603

Cites: 14

Cited by: 11

Related to: 10