An optimal algorithm for approximate nearest neighbor searching fixed dimensions
Journal of the ACM (JACM)
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
A Flexible Technique for Accurate Omnidirectional Camera Calibration and Structure from Motion
ICVS '06 Proceedings of the Fourth IEEE International Conference on Computer Vision Systems
Scalable Recognition with a Vocabulary Tree
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
MyPlaces: detecting important settings in a visual diary
CIVR '08 Proceedings of the 2008 international conference on Content-based image and video retrieval
Modeling the World from Internet Photo Collections
International Journal of Computer Vision
Combining image descriptors to effectively retrieve events from visual lifelogs
MIR '08 Proceedings of the 1st ACM international conference on Multimedia information retrieval
SenseCam Image Localisation Using Hierarchical SURF Trees
MMM '09 Proceedings of the 15th International Multimedia Modeling Conference on Advances in Multimedia Modeling
Accurate, Dense, and Robust Multiview Stereopsis
IEEE Transactions on Pattern Analysis and Machine Intelligence
The IMMED project: wearable video monitoring of people with age dementia
Proceedings of the international conference on Multimedia
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In this paper, a method for location recognition in a visual lifelog is presented. Its motivation is the detection of activity related places within an indoor environment to facilitate navigation in the lifelog. It takes advantage of a camera mounted on the shoulder, which is primarily designed for the behavioral analysis of Instrumental Activities of Daily Living (IADL). The proposed approach provides an automatic indexing of the content stream, based on the presence in specific 3D places related to instrumental activites. It relies on 3D models of the places of interest that are built thanks to a lightweight semi-supervised approach. Performance evaluation on real data show the potential of this approach compared to 2D only recognition.