TY - GEN
T1 - Improving a real-time object detector with compact temporal information
AU - Ahrnbom, Martin
AU - Jensen, Morten Bornø
AU - Åström, Kalle
AU - Nilsson, Mikael
AU - Ardö, Håkan
AU - Moeslund, Thomas B.
PY - 2017
Y1 - 2017
N2 - Neural networks designed for real-time object detection have recently improved significantly, but in practice, look- ing at only a single RGB image at the time may not be ideal. For example, when detecting objects in videos, a foreground detection algorithm can be used to obtain compact temporal data, which can be fed into a neural network alongside RGB images. We propose an approach for doing this, based on an existing object detector, that re-uses pretrained weights for the processing of RGB images. The neural network was tested on the VIRAT dataset with annotations for object de- tection, a problem this approach is well suited for. The ac- curacy was found to improve significantly (up to 66%), with a roughly 40% increase in computational time.
AB - Neural networks designed for real-time object detection have recently improved significantly, but in practice, look- ing at only a single RGB image at the time may not be ideal. For example, when detecting objects in videos, a foreground detection algorithm can be used to obtain compact temporal data, which can be fed into a neural network alongside RGB images. We propose an approach for doing this, based on an existing object detector, that re-uses pretrained weights for the processing of RGB images. The neural network was tested on the VIRAT dataset with annotations for object de- tection, a problem this approach is well suited for. The ac- curacy was found to improve significantly (up to 66%), with a roughly 40% increase in computational time.
U2 - 10.1109/ICCVW.2017.31
DO - 10.1109/ICCVW.2017.31
M3 - Article in proceeding
T3 - IEEE International Conference on Computer Vision Workshops (ICCVW)
SP - 190
EP - 197
BT - 2017 IEEE International Conference on Computer Vision Workshop (ICCVW): Computer Vision for Road Scene Understanding and Autonomous Driving workshop
PB - IEEE
T2 - 2017 IEEE International Conference on Computer Vision Workshop (ICCVW)
Y2 - 22 October 2017 through 29 October 2017
ER -