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https://www.um.edu.mt/library/oar/handle/123456789/23961
Title: | Fusion of intra- and inter-modality algorithms for face-sketch recognition |
Authors: | Galea, Christian Farrugia, Reuben A. |
Keywords: | Human face recognition (Computer science) Biometric identification -- Technological innovation |
Issue Date: | 2015 |
Publisher: | Springer |
Citation: | Galea, C., & Farrugia, R. A. (2015). Fusion of intra- and inter-modality algorithms for face-sketch recognition. 16th International Conference on Computer Analysis of Images and Patterns, Valletta. 700-711. |
Abstract: | Identifying and apprehending suspects by matching sketches created from eyewitness and victim descriptions to mugshot photos is a slow process since law enforcement agencies lack automated methods to perform this task. This paper attempts to tackle this problem by combining Eigentransformation, a global intra-modality approach, with the Eigenpatches local intra-modality technique. These algorithms are then fused with an inter-modality method called Histogram of Averaged Orientation Gradients (HAOG). Simulation results reveal that the intra- and inter- modality algorithms considered in this work provide complementary information since not only does fusion of the global and local intra-modality methods yield better performance than either of the algorithms individually, but fusion with the inter-modality approach yields further improvement to achieve retrieval rates of 94.05% at Rank-100 on 420 photo-sketch pairs. This performance is achieved at Rank-25 when filtering of the gallery using demographic information is carried out. |
URI: | https://www.um.edu.mt/library/oar//handle/123456789/23961 |
Appears in Collections: | Scholarly Works - FacICTCCE |
Files in This Item:
File | Description | Size | Format | |
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OACAIP15_v12.pdf | 1.11 MB | Adobe PDF | View/Open |
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