Assembling three one‐camera images for three‐camera intersection classification
Marcella Astrid,
Seung‐Ik Lee
Abstract:Determining whether an autonomous self‐driving agent is in the middle of an intersection can be extremely difficult when relying on visual input taken from a single camera. In such a problem setting, a wider range of views is essential, which drives us to use three cameras positioned in the front, left, and right of an agent for better intersection recognition. However, collecting adequate training data with three cameras poses several practical difficulties; hence, we propose using data collected from one cam… Show more
“…For this special issue, we selected 11 key studies on (1) communication, networks, and mobility [1][2][3][4][5] and (2) object detection and tracking in autonomous driving [6][7][8][9][10][11].…”
mentioning
confidence: 99%
“…In [11], three techniques for combining information from multiple cameras are proposed, namely, feature, early, and late fusion techniques. Extensive experiments were conducted on pedestrian-view intersection classification.…”
“…For this special issue, we selected 11 key studies on (1) communication, networks, and mobility [1][2][3][4][5] and (2) object detection and tracking in autonomous driving [6][7][8][9][10][11].…”
mentioning
confidence: 99%
“…In [11], three techniques for combining information from multiple cameras are proposed, namely, feature, early, and late fusion techniques. Extensive experiments were conducted on pedestrian-view intersection classification.…”
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