Automated Video-Based Traffic Count Analysis.

Taylor, C. J.; Kennedy, Ryan; Yang, Yuting; University of Pennsylvania; Delaware Valley Regional Planning Commission

Advanced Search

Select up to three search categories and corresponding keywords using the fields to the right. Refer to the Help section for more detailed instructions.

Search our Collections & Repository

Advanced Search
Custom Query

All these words:

For very narrow results

This exact word or phrase:

When looking for a specific result

Any of these words:

Best used for discovery & interchangable words

None of these words:

Recommended to be used in conjunction with other fields

Language:

Dates

Publication Date Range:

to

Document Data

Title:

Document Type:

Library

Collection:

Series:

People

Author:

Clear All

Query Builder

Query box

Clear All

For additional assistance using the Custom Query please check out our Help Page

i

Automated Video-Based Traffic Count Analysis.

2016
By Taylor, C. J. ; Kennedy, Ryan ; Yang, Yuting

[PDF-1.53 MB]

English

Details You May Also Like

Details:

Creators:

Taylor, C. J. ; Kennedy, Ryan ; Yang, Yuting

Taylor, C. J. ; Kennedy, Ryan ; Yang, Yuting Less -
Corporate Creators:

University of Pennsylvania ; Delaware Valley Regional Planning Commission

University of Pennsylvania ; Delaware Valley Regional Planning Commission Less -
Corporate Contributors:

Carnegie-Mellon University ; University Transportation Centers Program (U.S.)

Carnegie-Mellon University ; University Transportation Centers Program (U.S.) Less -
Subject/TRT Terms:

[+]

Automatic Data Collection Systems Traffic Counts Video Cameras Video Imaging Detectors
Resource Type:

Tech Report
Geographical Coverage:

United States
Corporate Publisher:

University Transportation Centers Program (U.S.)
Abstract:

The goal of this effort has been to develop techniques that could be applied to the

detection and tracking of vehicles in overhead footage of intersections. To that end we

have developed and published techniques for vehicle tracking based on detecting and

tracking point features. We showed how this approach could be combined with image

based background subtraction to find and group vehicles. In subsequent work we showed

how we could extract the 3D structure of a vehicle from a collection of feature tracks by

exploiting the non-linearities associated with the pinhole projection model.
Format:

PDF
Funding:

Contract No. DTRT12GUTG11
Collection(s):

University Transportation Centers US Transportation Collection
Main Document Checksum:

[+]

urn:sha256:4d9737de2dc7c723c4adbffa128646d3eeaf48f30a07b405df77f13e82a9f234
Download URL:

https://rosap.ntl.bts.gov/view/dot/31315/dot_31315_DS1.pdf
File Type:

No Additional Files

More +

Automated Video-Based Traffic Count Analysis.

Details:

Supporting Files

You May Also Like