TY - GEN
T1 - DEEP-CSSR
T2 - 23rd IEEE International Conference on Image Processing, ICIP 2016
AU - Qi, Mengshi
AU - Wang, Yunhong
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/8/3
Y1 - 2016/8/3
N2 - Researches in neuroscience and biological vision have shown that the bio-inspired methods have excellent recognition performance, such as the salient detection, artificial neural network and the ganglion cell inspired image feature. In this paper, we introduce a novel framework towards scene classification using category-specific salient region(CSSR) with deep CNN features, called Deep-CSSR. Firstly, by using the salient region detection algorithm, we extract a set of image patches which contain the salient regions. Also we apply DERF, a novel bio-inspired image descriptor, to represent the salient patches and clustering all of them to remove the outliers. Then we learn the CSSR filters and construct the CSSR representation. Further more, we do scene image classification using CSSR representation concatenate with the deep CNN features extracted from the whole images. By using this new pipeline, we obtain better results than recent methods over MIT Indoor 67 and Sun397 databases.
AB - Researches in neuroscience and biological vision have shown that the bio-inspired methods have excellent recognition performance, such as the salient detection, artificial neural network and the ganglion cell inspired image feature. In this paper, we introduce a novel framework towards scene classification using category-specific salient region(CSSR) with deep CNN features, called Deep-CSSR. Firstly, by using the salient region detection algorithm, we extract a set of image patches which contain the salient regions. Also we apply DERF, a novel bio-inspired image descriptor, to represent the salient patches and clustering all of them to remove the outliers. Then we learn the CSSR filters and construct the CSSR representation. Further more, we do scene image classification using CSSR representation concatenate with the deep CNN features extracted from the whole images. By using this new pipeline, we obtain better results than recent methods over MIT Indoor 67 and Sun397 databases.
KW - Deep CNN features
KW - Salient Region Detection
KW - Scene Classification
UR - https://www.scopus.com/pages/publications/85006788943
U2 - 10.1109/ICIP.2016.7532517
DO - 10.1109/ICIP.2016.7532517
M3 - 会议稿件
AN - SCOPUS:85006788943
T3 - Proceedings - International Conference on Image Processing, ICIP
SP - 1047
EP - 1051
BT - 2016 IEEE International Conference on Image Processing, ICIP 2016 - Proceedings
PB - IEEE Computer Society
Y2 - 25 September 2016 through 28 September 2016
ER -