Abstract
This paper presents a human detection system based on component detector using multiple feature descriptors. The contribution presents two issues for dealing with the problem of partially obscured human. First, it presents the extension of feature descriptors using multiple scales based Histograms of Oriented Gradients (HOG) and parallelogram based Haar-like feature (PHF) for improving the accuracy of the system. By using multiple scales based HOG, an extensive feature space allows obtaining high-discriminated features. Otherwise, the PHF is adaptive limb shapes of human in fast computing feature. Second, learning system using boosting classifications based approach is used for training and detecting the partially obscured human. The advantage of boosting is constructing a strong classification by combining a set of weak classifiers. However, the performance of boosting depends on the kernel of weak classifier. Therefore, the hybrid algorithms based on AdaBoost and SVM using the proposed feature descriptors is one of solutions for robust human detection.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Hoang, V.-D., Hernández, D.C., Le, M.-H., Jo, K.-H.: 3D Motion Estimation Based on Pitch and Azimuth from Respective Camera and Laser Rangefinder Sensing. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 735–740 (2013)
Hoang, V.-D., Hernández, D.C., Jo, K.-H.: Combining Edge and One-Point RANSAC Algorithm to Estimate Visual Odometry. In: Huang, D.-S., Bevilacqua, V., Figueroa, J.C., Premaratne, P. (eds.) ICIC 2013. LNCS, vol. 7995, pp. 556–565. Springer, Heidelberg (2013)
Dollar, P., Wojek, C., Schiele, B., Perona, P.: Pedestrian Detection: An Evaluation of the State of the Art. IEEE Transactions on Pattern Analysis and Machine Intelligence 34, 743–761 (2012)
Viola, P., Jones, M.J., Snow, D.: Detecting pedestrians using patterns of motion and appearance. In: International Conference on Computer Vision, pp. 734–741 (2003)
Munder, S., Gavrila, D.M.: An Experimental Study on Pedestrian Classification. IEEE Transactions on Pattern Analysis and Machine Intelligence 28, 1863–1868 (2006)
Hoang, V.-D., Vavilin, A., Jo, K.-H.: Fast Human Detection Based on Parallelogram Haar-Like Feature. In: The 38th Annual Conference of the IEEE Industrial Electronics Society, pp. 4220–4225 (2012)
Dalal, N., Triggs, B.: Histograms of oriented gradients for human detection. In: Conference on Computer Vision and Pattern Recognition, pp. 886–893 (2005)
Hoang, V.-D., Le, M.-H., Jo, K.-H.: Robust Human Detection Using Multiple Scale of Cell Based Histogram of Oriented Gradients and AdaBoost Learning. In: Nguyen, N.-T., Hoang, K., Jędrzejowicz, P. (eds.) Computational Collective Intelligence. Technologies and Applications. 7653, 61-71 (2012)
Hoang, V.-D., Le, M.-H., Jo, K.-H.: Hybrid Cascade Boosting Machine using Variant Scale Blocks based HOG Features for Pedestrian Detection. Neurocomputing 135, 357–366 (2014)
Wang, X., Han, T.X., Yan, S.: An HOG-LBP human detector with partial occlusion handling. In: International Conference on Computer Vision, pp. 32–39 (2009)
Schwartz, W.R., Gopalan, R., Chellappa, R., Davis, L.S.: Robust Human Detection under Occlusion by Integrating Face and Person Detectors. In: Tistarelli, M., Nixon, M.S. (eds.) ICB 2009. LNCS, vol. 5558, pp. 970–979. Springer, Heidelberg (2009)
Viola, P., Jones, M.J.: Robust Real-Time Face Detection. Intenational Journal of Computer Vision 57, 137–154 (2004)
Chih-Chung, C., Chih-Jen, L.: LIBSVM: a Library for Support Vector Machines. ACM Transactions on Intelligent Systems and Technology 2, 1–27 (2011)
Do, T.-N.: Parallel multiclass stochastic gradient descent algorithms for classifying million images with very-high-dimensional signatures into thousands classes. Vietnam Journal of Computer Science 1(2), 107–115 (2014), doi:10.1007/s40595-013-0013-2
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Hoang, VD., Hernandez, D.C., Jo, KH. (2014). Partially Obscured Human Detection Based on Component Detectors Using Multiple Feature Descriptors. In: Huang, DS., Bevilacqua, V., Premaratne, P. (eds) Intelligent Computing Theory. ICIC 2014. Lecture Notes in Computer Science, vol 8588. Springer, Cham. https://doi.org/10.1007/978-3-319-09333-8_37
Download citation
DOI: https://doi.org/10.1007/978-3-319-09333-8_37
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-09332-1
Online ISBN: 978-3-319-09333-8
eBook Packages: Computer ScienceComputer Science (R0)