Abstract
Understanding and semantic annotation of Human-Vehicle Interactions (HVI) facilitate fusion of Hard sensor (HS) and Human Intelligence (HUMINT) in a cohesive way. By characterization, classification, and discrimination of HVI patterns pertinent threats may be realized. Various Persistent Surveillance System (PSS) imagery techniques have been proposed in the past decade for identifying human interactions with various objects in the environment. Understanding of such interactions facilitates to discover human intentions and motives. However, without consideration of incidental context, reasoning and analysis of such behavioral activities is a very challenging and difficult task. This paper presents a current survey of related publications in the area of context-based Imagery techniques applied for HVI recognition, in particular, it discusses taxonomy and ontology of HVI and presents a summary of reported robust image processing techniques for spatiotemporal characterization and tracking of human targets in urban environments. The discussed techniques include model-based, shape-based and appearance-based techniques employed for identification and classification of objects. A detailed overview of major past research activities related to HVI in PSS with exploitation of spatiotemporal reasoning techniques applied to semantic labeling of the HVI is also presented.
| Original language | English (US) |
|---|---|
| Title of host publication | Signal Processing, Sensor Fusion, and Target Recognition XX |
| Volume | 8050 |
| DOIs | |
| State | Published - Jun 29 2011 |
| Event | Signal Processing, Sensor Fusion, and Target Recognition XX - Orlando, FL, United States Duration: Apr 25 2011 → Apr 27 2011 |
Other
| Other | Signal Processing, Sensor Fusion, and Target Recognition XX |
|---|---|
| Country | United States |
| City | Orlando, FL |
| Period | 4/25/11 → 4/27/11 |
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All Science Journal Classification (ASJC) codes
- Electronic, Optical and Magnetic Materials
- Condensed Matter Physics
- Computer Science Applications
- Applied Mathematics
- Electrical and Electronic Engineering
Cite this
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A survey of imagery techniques for semantic labeling of Human-Vehicle Interactions in persistent surveillance systems. / Elangovan, Vinayak; Shirkhodaie, Amir.
Signal Processing, Sensor Fusion, and Target Recognition XX. Vol. 8050 2011. 80501P.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - A survey of imagery techniques for semantic labeling of Human-Vehicle Interactions in persistent surveillance systems
AU - Elangovan, Vinayak
AU - Shirkhodaie, Amir
PY - 2011/6/29
Y1 - 2011/6/29
N2 - Understanding and semantic annotation of Human-Vehicle Interactions (HVI) facilitate fusion of Hard sensor (HS) and Human Intelligence (HUMINT) in a cohesive way. By characterization, classification, and discrimination of HVI patterns pertinent threats may be realized. Various Persistent Surveillance System (PSS) imagery techniques have been proposed in the past decade for identifying human interactions with various objects in the environment. Understanding of such interactions facilitates to discover human intentions and motives. However, without consideration of incidental context, reasoning and analysis of such behavioral activities is a very challenging and difficult task. This paper presents a current survey of related publications in the area of context-based Imagery techniques applied for HVI recognition, in particular, it discusses taxonomy and ontology of HVI and presents a summary of reported robust image processing techniques for spatiotemporal characterization and tracking of human targets in urban environments. The discussed techniques include model-based, shape-based and appearance-based techniques employed for identification and classification of objects. A detailed overview of major past research activities related to HVI in PSS with exploitation of spatiotemporal reasoning techniques applied to semantic labeling of the HVI is also presented.
AB - Understanding and semantic annotation of Human-Vehicle Interactions (HVI) facilitate fusion of Hard sensor (HS) and Human Intelligence (HUMINT) in a cohesive way. By characterization, classification, and discrimination of HVI patterns pertinent threats may be realized. Various Persistent Surveillance System (PSS) imagery techniques have been proposed in the past decade for identifying human interactions with various objects in the environment. Understanding of such interactions facilitates to discover human intentions and motives. However, without consideration of incidental context, reasoning and analysis of such behavioral activities is a very challenging and difficult task. This paper presents a current survey of related publications in the area of context-based Imagery techniques applied for HVI recognition, in particular, it discusses taxonomy and ontology of HVI and presents a summary of reported robust image processing techniques for spatiotemporal characterization and tracking of human targets in urban environments. The discussed techniques include model-based, shape-based and appearance-based techniques employed for identification and classification of objects. A detailed overview of major past research activities related to HVI in PSS with exploitation of spatiotemporal reasoning techniques applied to semantic labeling of the HVI is also presented.
UR - http://www.scopus.com/inward/record.url?scp=79959552172&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=79959552172&partnerID=8YFLogxK
U2 - 10.1117/12.887019
DO - 10.1117/12.887019
M3 - Conference contribution
SN - 9780819486240
VL - 8050
BT - Signal Processing, Sensor Fusion, and Target Recognition XX
ER -