Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Human Activity Recognition Using Multidimensional Indexing
IEEE Transactions on Pattern Analysis and Machine Intelligence
Implicit Probabilistic Models of Human Motion for Synthesis and Tracking
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Motion Activity Based Semantic Video Similarity Retrieval
PCM '02 Proceedings of the Third IEEE Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
Recognizing Human Actions: A Local SVM Approach
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
A Quick Video Search Method based on Local and Global Feature Clustering
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
International Journal of Computer Vision
Near-Optimal Hashing Algorithms for Approximate Nearest Neighbor in High Dimensions
FOCS '06 Proceedings of the 47th Annual IEEE Symposium on Foundations of Computer Science
IEEE Transactions on Pattern Analysis and Machine Intelligence
Tiny Videos: Non-parametric Content-Based Video Retrieval and Recognition
ISM '08 Proceedings of the 2008 Tenth IEEE International Symposium on Multimedia
Semantic Event Retrieval from Surveillance Video Databases
ISM '08 Proceedings of the 2008 Tenth IEEE International Symposium on Multimedia
Nonlinear Mean Shift over Riemannian Manifolds
International Journal of Computer Vision
International Journal of Approximate Reasoning
Nearest-neighbor search algorithms on non-Euclidean manifolds for computer vision applications
Proceedings of the Seventh Indian Conference on Computer Vision, Graphics and Image Processing
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part III
Image and Vision Computing
Conjugate gradient on Grassmann manifolds for robust subspace estimation
Image and Vision Computing
Advances in matrix manifolds for computer vision
Image and Vision Computing
Linear cross-modal hashing for efficient multimedia search
Proceedings of the 21st ACM international conference on Multimedia
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Approximate Nearest Neighbor (ANN) methods such as Locality Sensitive Hashing, Semantic Hashing, and Spectral Hashing, provide computationally efficient procedures for finding objects similar to a query object in large datasets. These methods have been successfully applied to search web-scale datasets that can contain millions of images. Unfortunately, the key assumption in these procedures is that objects in the dataset lie in a Euclidean space. This assumption is not always valid and poses a challenge for several computer vision applications where data commonly lies in complex non-Euclidean manifolds. In particular, dynamic data such as human activities are commonly represented as distributions over bags of video words or as dynamical systems. In this paper, we propose two new algorithms that extend Spectral Hashing to non-Euclidean spaces. The first method considers the Riemannian geometry of the manifold and performs Spectral Hashing in the tangent space of the manifold at several points. The second method divides the data into subsets and takes advantage of the kernel trick to perform non-Euclidean Spectral Hashing. For a data set of N samples the proposed methods are able to retrieve similar objects in as low as O(K) time complexity, where K is the number of clusters in the data. Since K ≪ N, our methods are extremely efficient. We test and evaluate our methods on synthetic data generated from the Unit Hypersphere and the Grassmann manifold. Finally, we show promising results on a human action database.