Mr. Bob P.W. van den Hoogen Profile

Bob P.W. van den Hoogen

at TNO

SPIE Involvement:

Author

Publications (1)

This will count as one of your downloads.

You will have access to both the presentation and article (if available).

DOWNLOAD NOW

This content is available for download via your institution's subscription. To access this item, please sign in to your personal account.

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

Proceedings Article | 20 September 2020 Presentation + Paper

Long-range person and vehicle detection

Bob van den Hoogen, Wouter Uijens, Richard den Hollander, Wyke Huizinga, Judith Dijk, Klamer Schutte

Proceedings Volume 11543, 115430B (2020) https://doi.org/10.1117/12.2582373

Read Abstract +

Automatic detection and tracking of persons and vehicles can greatly increase situational awareness in many military applications. Various methods for detection and tracking have been proposed so far, both for rule-based and learning approaches. With the advent of deep learning, learning approaches generally outperform rule-based approaches. Pre-trained neural networks on datasets like MS COCO can give reasonable detection performance on military datasets. However, for optimal performance it is advised to optimize the training of these pre-trained networks with a representative dataset. In typical military settings, it is a challenge to acquire enough data, and to split the training and test set properly. In this paper we evaluate fine-tuning on military data and compare different pre- and post-processing methods. First we compare a standard pre-trained RetinaNet detector with a fine-tuned version, trained on similar objects, which are recorded at distances different than the distance in the test set. On the aspect of distance this train set is therefore out-of-distribution. Next, we augment the training examples by both increasing and decreasing their size. Once detected, we use a template tracker to follow the objects, compensating for any missing detections. We show the results on detection and tracking of persons and vehicles in visible imagery in a military long range detection setting. The results show the added value of fine-tuning a neural net with augmented examples, where final network performance is similar to human visual performance for detection of targets, with a target area of tens of pixels in a moderately cluttered land environment.

My Library

You currently do not have any folders to save your paper to! Create a new folder below.

Folder Name

Folder Description

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks. You are receiving this notice because your organization may not have SPIE eBooks access.*

*Shibboleth/Open Athens users─please sign in to access your institution's subscriptions.

To obtain this item, you may purchase the complete book in print or electronic format on SPIE.org.

ORGANIZATIONAL
Sign in with credentials provided by your organization.

Organizational Username

Organizational Password

Show/Hide Password

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members:

Non-members: ADD TO CART

Keywords/Phrases

Search In:

Publication Years