A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Probabilistic latent semantic indexing
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
An Affine Invariant Interest Point Detector
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
CBAIVL '00 Proceedings of the IEEE Workshop on Content-based Access of Image and Video Libraries (CBAIVL'00)
The Journal of Machine Learning Research
Video Google: A Text Retrieval Approach to Object Matching in Videos
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Shape Matching and Object Recognition Using Low Distortion Correspondences
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Histograms of Oriented Gradients for Human Detection
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Discovering Objects and their Localization in Images
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Object Categorization by Learned Universal Visual Dictionary
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Using Multiple Segmentations to Discover Objects and their Extent in Image Collections
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Hamming Embedding and Weak Geometric Consistency for Large Scale Image Search
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
Building compact local pairwise codebook with joint feature space clustering
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part I
What makes Paris look like Paris?
ACM Transactions on Graphics (TOG) - SIGGRAPH 2012 Conference Proceedings
Visual pattern discovery for architecture image classification and product image search
Proceedings of the 2nd ACM International Conference on Multimedia Retrieval
Image matching using local symmetry features
CVPR '12 Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Three things everyone should know to improve object retrieval
CVPR '12 Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Smooth object retrieval using a bag of boundaries
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
Compact correlation coding for visual object categorization
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
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Instance retrieval has emerged as a promising research area with buildings as the popular test subject. Given a query image or region, the objective is to find images in the database containing the same object or scene. There has been a recent surge in efforts in finding instances of the same building in challenging datasets such as the Oxford 5k dataset [19], Oxford 100k dataset and the Paris dataset [20]. We ascend one level higher and pose the question: Are Buildings Only Instances? Buildings located in the same geographical region or constructed in a certain time period in history often follow a specific method of construction. These architectural styles are characterized by certain features which distinguish them from other styles of architecture. We explore, beyond the idea of buildings as instances, the possibility that buildings can be categorized based on the architectural style. Certain characteristic features distinguish an architectural style from others. We perform experiments to evaluate how characteristic information obtained from low-level feature configurations can help in classification of buildings into architectural style categories. Encouraged by our observations, we mine characteristic features with semantic utility for different architectural styles from our dataset of European monuments. These mined features are of various scales, and provide an insight into what makes a particular architectural style category distinct. The utility of the mined characteristics is verified from Wikipedia.