Automatic vehicle tracking and recognition from aerial image sequences

06/23/2015
by   Ognjen Arandjelovic, et al.
0

This paper addresses the problem of automated vehicle tracking and recognition from aerial image sequences. Motivated by its successes in the existing literature focus on the use of linear appearance subspaces to describe multi-view object appearance and highlight the challenges involved in their application as a part of a practical system. A working solution which includes steps for data extraction and normalization is described. In experiments on real-world data the proposed methodology achieved promising results with a high correct recognition rate and few, meaningful errors (type II errors whereby genuinely similar targets are sometimes being confused with one another). Directions for future research and possible improvements of the proposed method are discussed.

READ FULL TEXT

page 3

page 4

research
09/01/2021

An Automated Approach for the Recognition of Bengali License Plates

Automatic Number Plate Recognition (ALPR) is a system for automatically ...
research
06/29/2020

Vehicle Attribute Recognition by Appearance: Computer Vision Methods for Vehicle Type, Make and Model Classification

This paper studies vehicle attribute recognition by appearance. In the l...
research
04/13/2016

Online Multi-Target Tracking Using Recurrent Neural Networks

We present a novel approach to online multi-target tracking based on rec...
research
10/19/2020

Multiple Pedestrians and Vehicles Tracking in Aerial Imagery: A Comprehensive Study

In this paper, we address various challenges in multi-pedestrian and veh...
research
08/01/2022

Local Perception-Aware Transformer for Aerial Tracking

Transformer-based visual object tracking has been utilized extensively. ...
research
01/31/2014

Hallucinating optimal high-dimensional subspaces

Linear subspace representations of appearance variation are pervasive in...

Please sign up or login with your details

Forgot password? Click here to reset