Abstract
Over 30 years of psychological studies on eyewitness testimonies procedures show severe flaws including ignoring human face perception biases that render these procedures unreliable. In addition, recent studies show that current automatic face sketch recognition methods are only tested on over simplified databases, and therefore cannot address the real cases. We here present a face sketch recognition method based on non-artistic sketches in which we firstly estimate and remove personal face perception biases from face sketches, and then recognize them based on a psychologically inspired matching technique. In addition, we use a general-specific modeling that only needs a few training samples for each individual for an accurate and robust performance. In our experiments, we tested accuracy and robustness against previous works, and the effect of number of training samples on the accuracy of our method.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Toglia, M.P., Read, J.D., Ross, D.F., Lindsay, R.: Handbook of Eyewitness Psychology: Memory for events. Lawrence Erlbaum Associates (2007)
Sinha, P., Balas, B., Ostrovsky, Y., Russell, R.: Face recognition by humans: Nineteen results all computer vision researchers should know about. Proc. IEEE 94(11), 1948–1962 (2006)
Carlson, C., Gronlund, S., Clark, S.: Lineup composition, suspect position, and the sequential lineup advantage. J. Exp. Psychol. Appl. 14(2), 118–128 (2008)
Klare, B., Li, Z., Jain, A.: Matching forensic sketches to mug shot photos. IEEE Transactions on Pattern Analysis and Machine Intelligence 33, 639–646 (2011)
Sinha, P., Balas, B.J., Ostrovsky, Y., Russell, R.: Face recognition by humans. Face Recognition: Models and Mechanisms (2006)
Wang, X., Tang, X.: Face photo-sketch synthesis and recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence 31, 1955–1967 (2009)
Tang, X., Wang, X.: Face sketch recognition. T-CSVT 14, 50–57 (2004)
Zhang, Y., McCullough, C., Sullins, J., Ross, C.: Hand-drawn face sketch recognition by humans and a pca-based algorithm for forensic applications. SMC-A 40, 475–485 (2010)
Nejati, H., Sim, T., Martinez-Marroquin, E.: Do you see what i see?: A more realistic eyewitness sketch recognition. IJCB (2011)
Choi, J., Sharma, A., Jacobs, D., Davis, L.: Data insufficiency in sketch versus photo face recognition. In: 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 1–8 (2012)
Li, Y.H., Savvides, M., Bhagavatula, V.: Illumination tolerant face recognition using a novel face from sketch synthesis approach and advanced correlation filters. In: ICASSP 2006, vol. 2, pp. II –II, 14-19 (2006)
Liu, Q., Tang, X., Jin, H., Lu, H., Ma, S.: A nonlinear approach for face sketch synthesis and recognition. In: CVPR 2005, vol. 1, pp. 1005–1010, 20-25 (2005)
Xiao, B., Gao, X., Tao, D., Li, X.: A new approach for face recognition by sketches in photos. Signal Process 89(8), 1576–1588 (2009)
Sharma, A., Jacobs, D.: Bypassing synthesis: Pls for face recognition with pose, low-resolution and sketch. In: 2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 593–600 (2011)
Zhang, W., Wang, X., Tang, X.: Coupled information-theoretic encoding for face photo-sketch recognition. In: 2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 513–520 (2011)
Zhang, J., Wang, N., Gao, X., Tao, D., Li, X.: Face sketch-photo synthesis based on support vector regression. In: 2011 18th IEEE International Conference on Image Processing (ICIP), pp. 1125–1128 (2011)
Galoogahi, H., Sim, T.: Inter-modality face sketch recognition. In: 2012 IEEE International Conference on Multimedia and Expo (ICME), pp. 224–229 (2012)
Facevacs software developer kit, cognitec systems gmbh(2010), http://www.cognitec-systems.de
Milborrow, S., Nicolls, F.: Locating facial features with an extended active shape model. In: Forsyth, D., Torr, P., Zisserman, A. (eds.) ECCV 2008, Part IV. LNCS, vol. 5305, pp. 504–513. Springer, Heidelberg (2008)
Fritsch, F.N., Carlson, R.E.: Monotone piecewise cubic interpolation. S-INUM 17, 238–246 (1980)
Unnikrishnan, M.: How is the individuality of a face recognized? J. Theor. Biol. 261(3), 469–474 (2009)
Arandjelovic, O., Cipolla, R.: An information-theoretic approach to face recognition from face motion manifolds. Image and Vision Computing 24(6), 639–647 (2006); Face Processing in Video Sequences
Gross, R., Matthews, I., Cohn, J., Kanade, T., Baker, S.: Multi-pie. In: FG 2008, pp. 1–8 (September 2008)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Nejati, H., Zhang, L., Sim, T. (2013). Eyewitness Face Sketch Recognition Based on Two-Step Bias Modeling. In: Wilson, R., Hancock, E., Bors, A., Smith, W. (eds) Computer Analysis of Images and Patterns. CAIP 2013. Lecture Notes in Computer Science, vol 8048. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40246-3_4
Download citation
DOI: https://doi.org/10.1007/978-3-642-40246-3_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-40245-6
Online ISBN: 978-3-642-40246-3
eBook Packages: Computer ScienceComputer Science (R0)