Boyraz et al 2011a - Revision history

Scipediacontent at 15:05, 21 January 2021

2021-01-21T15:05:20Z

Scipediacontent: Scipediacontent moved page Draft Content 908755537 to Boyraz et al 2011a

2020-10-14T12:08:37Z

Scipediacontent moved page Draft Content 908755537 to Boyraz et al 2011a

Scipediacontent: Created page with " == Abstract == Recent developments of information technology and mobile lifestyle have forced drivers to multitask while they drive. The in-vehicle infotainment technolo..."

2020-10-14T12:08:34Z

Created page with " == Abstract == Recent developments of information technology and mobile lifestyle have forced drivers to multitask while they drive. The in-vehicle infotainment technolo..."

New page

== Abstract ==

Recent developments of information technology and mobile lifestyle have forced drivers to multitask while they drive. The in-vehicle infotainment technology is already taking its place in the transformation of vehicles towards more intelligent and interactive devices rather than staying as mere transportation convenience. This transformation has several advantages such as easy route navigation, real-time traffic information, and staying connected with work or people while traveling. However, it has several drawbacks concerning the impact on driver cognitive load and attention sources. Therefore, it is crucial to take advantage of state-of-the-art in-vehicle technology to produce counter-measure systems that monitor the driver status and reduce driver workload adaptively depending on the context. In recognition and analysis of the driving context together with driver status monitoring, computer vision applications supply crucial information both in the vehicle (i.e., driver head and eye tracking) and out of the vehicle (i.e., lane, pedestrian, and vehicle detection and tracking, and road sign recognition). In this chapter, we provide a broad range of computer vision applications for CA-IVS from the literature and our previous studies, and we report our current research efforts.

Document type: Part of book or chapter of book

== Full document ==
<pdf>Media:Draft_Content_908755537-beopen472-3387-document.pdf</pdf>

== Original document ==

The different versions of the original document can be found in:

* [http://www-nrd.nhtsa.dot.gov/pdf/esv/esv21/09-0266.pdf http://www-nrd.nhtsa.dot.gov/pdf/esv/esv21/09-0266.pdf]

@@ Line 2: / Line 2: @@
 == Abstract ==
-Recent developments of information technology and mobile lifestyle have forced drivers to multitask while they drive. The in-vehicle infotainment technology is already taking its place in the transformation of vehicles towards more intelligent and interactive devices rather than staying as mere transportation convenience. This transformation has several advantages such as easy route navigation, real-time traffic information, and staying connected with work or people while traveling. However, it has several drawbacks concerning the impact on driver cognitive load and attention sources. Therefore, it is crucial to take advantage of state-of-the-art in-vehicle technology to produce counter-measure systems that monitor the driver status and reduce driver workload adaptively depending on the context. In recognition and analysis of the driving context together with driver status monitoring, computer vision applications supply crucial information both in the vehicle (i.e., driver head and eye tracking) and out of the vehicle (i.e., lane, pedestrian, and vehicle detection and tracking, and road sign recognition). In this chapter, we provide a broad range of computer vision applications for CA-IVS from the literature and our previous studies, and we report our current research efforts.
+Recent developments of information technology and mobile lifestyle have forced drivers to multitask while they drive. The in-vehicle âinfotainmentâ technology is already taking its place in the transformation of vehicles towards more intelligent and interactive devices rather than staying as mere transportation convenience. This transformation has several advantages such as easy route navigation, real-time traffic information, and staying connected with work or people while traveling. However, it has several drawbacks concerning the impact on driver cognitive load and attention sources. Therefore, it is crucial to take advantage of state-of-the-art in-vehicle technology to produce counter-measure systems that monitor the driver status and reduce driver workload adaptively depending on the context. In recognition and analysis of the driving context together with driver status monitoring, computer vision applications supply crucial information both in the vehicle (i.e., driver head and eye tracking) and out of the vehicle (i.e., lane, pedestrian, and vehicle detection and tracking, and road sign recognition). In this chapter, we provide a broad range of computer vision applications for CA-IVS from the literature and our previous studies, and we report our current research efforts.
-−
-Document type: Part of book or chapter of book
-−
-== Full document ==
-<pdf>Media:Draft_Content_908755537-beopen472-3387-document.pdf</pdf>
@@ Line 15: / Line 10: @@
 * [http://www-nrd.nhtsa.dot.gov/pdf/esv/esv21/09-0266.pdf http://www-nrd.nhtsa.dot.gov/pdf/esv/esv21/09-0266.pdf]

← Older revision	Revision as of 12:08, 14 October 2020
(No difference)

Boyraz et al 2011a - Revision history

Scipediacontent at 15:05, 21 January 2021

Scipediacontent: Scipediacontent moved page Draft Content 908755537 to Boyraz et al 2011a

Scipediacontent: Created page with " == Abstract == Recent developments of information technology and mobile lifestyle have forced drivers to multitask while they drive. The in-vehicle infotainment technolo..."

Scipediacontent: Created page with " == Abstract == Recent developments of information technology and mobile lifestyle have forced drivers to multitask while they drive. The in-vehicle infotainment technolo..."