Sparse Detector Imaging Sensor with Two-Class Silhouette Classification Article Swipe
David J. Russomanno
,
Srikant Chari
,
Carl E. Halford
·
YOU?
·
· 2008
· Open Access
·
· DOI: https://doi.org/10.3390/s8127996
YOU?
·
· 2008
· Open Access
·
· DOI: https://doi.org/10.3390/s8127996
This paper presents the design and test of a simple active near-infrared sparse detector imaging sensor. The prototype of the sensor is novel in that it can capture remarkable silhouettes or profiles of a wide-variety of moving objects, including humans, animals, and vehicles using a sparse detector array comprised of only sixteen sensing elements deployed in a vertical configuration. The prototype sensor was built to collect silhouettes for a variety of objects and to evaluate several algorithms for classifying the data obtained from the sensor into two classes: human versus non-human. Initial tests show that the classification of individually sensed objects into two classes can be achieved with accuracy greater than ninety-nine percent (99%) with a subset of the sixteen detectors using a representative dataset consisting of 512 signatures. The prototype also includes a Webservice interface such that the sensor can be tasked in a network-centric environment. The sensor appears to be a low-cost alternative to traditional, high-resolution focal plane array imaging sensors for some applications. After a power optimization study, appropriate packaging, and testing with more extensive datasets, the sensor may be a good candidate for deployment in vast geographic regions for a myriad of intelligent electronic fence and persistent surveillance applications, including perimeter security scenarios.
Related Topics
Concepts
Detector
Computer science
Silhouette
Artificial intelligence
Image sensor
Wireless sensor network
Software deployment
Computer vision
Sensor array
Interface (matter)
Real-time computing
Machine learning
Bubble
Operating system
Maximum bubble pressure method
Telecommunications
Parallel computing
Computer network
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/s8127996
- https://www.mdpi.com/1424-8220/8/12/7996/pdf?version=1403310699
- OA Status
- gold
- Cited By
- 23
- References
- 16
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2105884214
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W2105884214Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/s8127996Digital Object Identifier
- Title
-
Sparse Detector Imaging Sensor with Two-Class Silhouette ClassificationWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2008Year of publication
- Publication date
-
2008-12-08Full publication date if available
- Authors
-
David J. Russomanno, Srikant Chari, Carl E. HalfordList of authors in order
- Landing page
-
https://doi.org/10.3390/s8127996Publisher landing page
- PDF URL
-
https://www.mdpi.com/1424-8220/8/12/7996/pdf?version=1403310699Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.mdpi.com/1424-8220/8/12/7996/pdf?version=1403310699Direct OA link when available
- Concepts
-
Detector, Computer science, Silhouette, Artificial intelligence, Image sensor, Wireless sensor network, Software deployment, Computer vision, Sensor array, Interface (matter), Real-time computing, Machine learning, Bubble, Operating system, Maximum bubble pressure method, Telecommunications, Parallel computing, Computer networkTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
23Total citation count in OpenAlex
- Citations by year (recent)
-
2023: 1, 2020: 1, 2019: 1, 2016: 1, 2015: 2Per-year citation counts (last 5 years)
- References (count)
-
16Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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