Abstract
Automatic face recognition capability in surveillance systems is important for security applications. However, few studies have addressed the problem of outdoor face recognition at a long distance (over 100 meters) in both daytime and nighttime environments. In this paper, we first report on a system that we have designed to collect face image database at a long distance, called the Long Distance Heterogeneous Face Database (LDHF-DB) to advance research on this topic. The LDHF-DB contains face images collected in an outdoor environment at distances of 60 meters, 100 meters, and 150 meters, with both visible light (VIS) face images captured in daytime and near infrared (NIR) face images captured in nighttime. Given this database, we have conducted two types of cross-distance face matching (matching long-distance probe to 1-meter gallery) experiments: (i) intra-spectral (VIS to VIS) face matching, and (ii) cross-spectral (NIR to VIS) face matching. The proposed face recognition algorithm consists of following three major steps: (i) Gaussian filtering to remove high frequency noise, (ii) Scale Invariant Feature Transform (SIFT) in local image regions for feature representation, and (iii) a random subspace method to build discriminant subspaces for face recognition. Experimental results show that the proposed face recognition algorithm outperforms two commercial state-of-the-art face recognition SDKs (FaceVACS and PittPatt) for long distance face recognition in both daytime and nighttime operations. These results highlight the need for better data capture setup and robust face matching algorithms for cross spectral matching at distances greater than 100 meters.
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References
Mail Online: Big Brother is DEFINITELY watching you: Shocking study reveals UK has one CCTV for every 32 people (2011)
Phillips, P.J., Flynn, P.J., Beveridge, J.R., Scruggs, W.T., O’Toole, A.J., Bolme, D., Bowyer, K.W., Draper, B.A., Givens, G.H., Lui, Y.M., Sahibzada, H., Scallan III, J.A., Weimer, S.: Overview of the Multiple Biometrics Grand Challenge. In: Tistarelli, M., Nixon, M.S. (eds.) ICB 2009. LNCS, vol. 5558, pp. 705–714. Springer, Heidelberg (2009)
Rara, H., Ali, A., Elhabian, S., Starr, T., Farag, A.: Face Recognition at-a-Distance Using Texture, Dense- and Sparse-Stereo Reconstruction. In: Proceedings of 20th International Conference on Pattern Recognition, pp. 1221–1224 (2010)
Huang, D., Wang, Y., Wang, Y.: A Robust Method for Near Infrared Face Recognition Based on Extended Local Binary Pattern. In: Bebis, G., Boyle, R., Parvin, B., Koracin, D., Paragios, N., Tanveer, S.-M., Ju, T., Liu, Z., Coquillart, S., Cruz-Neira, C., Müller, T., Malzbender, T. (eds.) ISVC 2007, Part II. LNCS, vol. 4842, pp. 437–446. Springer, Heidelberg (2007)
Zou, X., Kittler, J., Messer, K.: Illumination invariant face recognition: A survey. In: First IEEE International Conference on Biometrics Theory Applications and Systems, pp. 1–8 (2007)
Morimoto, C.H., Flickner, M.: Real-time multiple face detection using active illumination. In: IEEE International Conference on Automatic Face and Gesture Recognition, pp. 8–13 (2000)
Pan, Z., Healey, G.E., Prasad, M., Tromberg, B.J.: Face recognition in hyperspectral images. IEEE Transactions on Pattern Analysis and Machine Intelligence 25, 1552–1560 (2003)
Li, D.Y., Liao, W.H.: Facial feature detection in near-infrared images. In: Proceedings of 5th International Conference on Computer Vision, Pattern Recognition and Image Processing, pp. 26–30 (2003)
Dowdall, J., Pavlidis, I., Bebis, G.: Face detection in the near-ir spectrum. Image and Vision Computing 21, 565–578 (2003)
Zhao, S., Grigat, R.R.: An automatic face recognition system in the near infrared spectrum. In: Proceedings of the 4th International Conference on Machine Learning and Data Mining in Pattern Recognition, pp. 437–444 (2005)
Shen, L., He, J., Wu, S., Zheng, S.: Face Recognition from Visible and Near-Infrared Images Using Boosted Directional Binary Code. In: Huang, D.-S., Gan, Y., Gupta, P., Gromiha, M.M. (eds.) ICIC 2011. LNCS, vol. 6839, pp. 404–411. Springer, Heidelberg (2012)
Li, S.Z., Chu, R., Liao, S., Zhang, L.: Illumination invariant face recognition using near-infrared images. IEEE Transactions on Pattern Analysis and Machine Intelligence 29, 627–639 (2007)
Zhang, B., Zhang, L., Zhang, D., Shen, L.: Directional binary code with application to polyu near-infrared face database. Pattern Recognition Letters 31, 2337–2344 (2010)
Chen, J., Yi, D., Yang, J., Zhao, G., Li, S.Z., Pietikäinen, M.: Learning mappings for face synthesis from near infrared to visual light images. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 156–163 (2009)
Wang, R., Yang, J., Yi, D., Li, S.Z.: An Analysis-by-Synthesis Method for Heterogeneous Face Biometrics. In: Tistarelli, M., Nixon, M.S. (eds.) ICB 2009. LNCS, vol. 5558, pp. 319–326. Springer, Heidelberg (2009)
Yi, D., Liu, R., Chu, R., Lei, Z., Li, S.Z.: Face Matching Between Near Infrared and Visible Light Images. In: Lee, S.-W., Li, S.Z. (eds.) ICB 2007. LNCS, vol. 4642, pp. 523–530. Springer, Heidelberg (2007)
Liao, S., Yi, D., Lei, Z., Qin, R., Li, S.Z.: Heterogeneous Face Recognition from Local Structures of Normalized Appearance. In: Tistarelli, M., Nixon, M.S. (eds.) ICB 2009. LNCS, vol. 5558, pp. 209–218. Springer, Heidelberg (2009)
Klare, B., Jain, A.K.: Heterogeneous face recognition: Matching NIR to visible light images. In: International Conference on Pattern Recognition, pp. 1513–1516 (2010)
Maeng, H., Choi, H.C., Park, U., Lee, S.W., Jain, A.K.: NFRAD: Near-infrared face recognition at a distance. In: International Joint Conference on Biometrics, pp. 1–7 (2011)
Bourlai, T., VonDollen, J., Kolanko, C.: Evaluating the efficiency of a night-time, middle-range infrared sensor for applications in human detection and recognition. In: Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXIII (2012)
Yao, Y., Abidi, B.R., Kalka, N.D., Schmid, N.A., Abidi, M.A.: Improving long range and high magnification face recognition: Database acquisition, evaluation, and enhancement. Computer Vision and Image Understanding 111, 111–125 (2008)
Li, S.Z., Yi, D.: Face recognition using near infrared images. In: Li, S.Z., Jain, A.K. (eds.) Handbook of Face Recognition, pp. 383–400. Springer (2011)
Lowe, D.: Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision 60, 91–110 (2004)
Li, S.Z., Lei, Z., Ao, M.: The HFB face database for heterogeneous face biometrics research. In: Computer Vision and Pattern Recognition Workshop, pp. 1–8 (2009)
FaceVACS Software Developer Kit, Cognitec Systems GmbH, http://www.cognitec-systems.de
PittPatt Software Developer Kit, Pittsburgh Pattern Recognition, Inc., http://www.pittpatt.com
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Maeng, H., Liao, S., Kang, D., Lee, SW., Jain, A.K. (2013). Nighttime Face Recognition at Long Distance: Cross-Distance and Cross-Spectral Matching. In: Lee, K.M., Matsushita, Y., Rehg, J.M., Hu, Z. (eds) Computer Vision – ACCV 2012. ACCV 2012. Lecture Notes in Computer Science, vol 7725. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37444-9_55
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DOI: https://doi.org/10.1007/978-3-642-37444-9_55
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