Mining Compositional Features From GPS and Visual Cues for Event Recognition in Photo Collections

As digital cameras with Global Positioning System (GPS) capability become available and people geotag their photos using other means, it is of great interest to annotate semantic events (e.g., hiking, skiing, party) characterized by a collection of geotagged photos with timestamps and GPS information at the capture. We address this emerging event classification problem by mining informative features derived from image contents and spatio-temporal traces of GPS coordinates that characterize the underlying movement patterns of various event types, both based on the entire collection as opposed to individual photos. Considering that events are better described by the co-occurrence of objects and scenes, we bundle primitive features such as color and texture histograms or GPS features to form the discriminative compositional feature. A data mining method is proposed to efficiently discover discriminative compositional features of small classification errors. A theoretical analysis is also ...

• Type: Journal
• Year: 2010
• Where: TMM
• Authors: Junsong Yuan, Jiebo Luo, Ying Wu
• Keywords: Compositional Features, Discriminative Compositional Features, Management, Mining, TMM 2010