Efficient Web-based Facial Recognition System Employing 2DHOG
This addresses the specific problem of identifying individuals in large crowds during religious pilgrimages, though it appears incremental as it builds on existing techniques like HOG and PCA.
The paper tackles facial recognition for identifying missing/found people during Hajj and Umrah by developing a web portal system that uses a novel algorithm combining 2DPCA with 2D-HOG to maintain spatial relations, achieving the highest reported recognition accuracy while reducing computational complexity and storage requirements.
In this paper, a system for facial recognition to identify missing and found people in Hajj and Umrah is described as a web portal. Explicitly, we present a novel algorithm for recognition and classifications of facial images based on applying 2DPCA to a 2D representation of the Histogram of oriented gradients (2D-HOG) which maintains the spatial relation between pixels of the input images. This algorithm allows a compact representation of the images which reduces the computational complexity and the storage requirments, while maintaining the highest reported recognition accuracy. This promotes this method for usage with very large datasets. Large dataset was collected for people in Hajj. Experimental results employing ORL, UMIST, JAFFE, and HAJJ datasets confirm these excellent properties.