Automatic identification of "who" is present in individual digital images within a photo management system using only content-based analysis is an extremely difficult problem. We present a system which enables identification of person reoccurrences within a personal photo management application by combining image content-based analysis tools with context data from image capture. This combined system employs automatic face detection and body-patch matching techniques, which collectively facilitate identifying person re-occurrences within images grouped into events based on context data. We introduce a face detection approach combining a histogrambased skin detection model and a modified BDF face detection method to detect multiple frontal faces in colour images. Corresponding body patches are then automatically segmented relative to the size, location and orientation of the detected faces in the image. We investigate the suitability of using different colour descriptors, including MPEG-7 colour descriptors, Color Coherent Vectors (CCV) and Color Correlograms for effective body-patch matching. The system has been successfully integrated into the MediAssist platform, a prototype web-based system for personal photo management, and runs on over 13000 personal photos.
Body-patch segments are extracted relative to automatic face detection results as described in REF .
Identifying person re-occurrences for personal photo management applications
In VIE 2006
Geography