The week's pick
Random Articles
Reseach Article
Scale Invariant static hand-postures detection using Extended Higher-order Local Autocorrelation features
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 135 - Number 5 |
| Year of Publication: 2016 |
| Authors: Isack Bulugu, Zhongfu Ye |
10.5120/ijca2016904742
|
Isack Bulugu, Zhongfu Ye . Scale Invariant static hand-postures detection using Extended Higher-order Local Autocorrelation features. International Journal of Computer Applications. 135, 5 ( February 2016), 1-5. DOI=10.5120/ijca2016904742
Abstract
This paper presents scale invariant static hand postures detection methods using extended HLAC features extractedfrom Log-Polar images. Scale changes of a handposture in an image are represented as shift in Log-Polar image. Robustness of the method is achieved through extracting spectral features from theeach row of the Log-Polar image. Linear Discriminant Analysis was used to combine features with simple classification methods in order to realize scale invariant hand postures detection and classification.The method was successful tested by performing experiment using NSU hand posture dataset images which consists 10 classes of postures, 24 samples of images per class, which are captured by the position and size of the hand within the image frame. The results showed that the detection rate using Extended-HLAC can averaged reach 94.63% higher than using HLAC features on a Intel Core i5-4590 CPU running at 3.3 GHz.
References
- Vladimir I. Pavlovic, Rajeev Sharma, Thomas S. Huang Visual interpretation of hand gestures for human–computer interaction IEEE Trans. Pattern Anal. Mach. Intell., 19 (6) (1997), pp. 677–695
- S.C.W. Ong, S. RanganathAutomatic sign language analysis: a survey and the future beyond lexical meaning IEEE Transactions on Pattern Analysis and Machine Intelligence, 27 (6) (2005), pp. 873–891 View Record in ScopusFull Text via CrossRefCiting articles (223)
- N. Otsu, T. Kurita, A new scheme for practical flexible and intelligent vision systems, in: Proceedings of the IAPR Workshop on Computer Vision, 1988, pp. 431–435.
- T. Kurita, N. Otsu, T. Sato, A face recognition method using higher order local autocorrelation and multivariate analysis, in: Proceedings of the International Conference on Pattern Recognition, vol. 2, 1992, pp. 213–216.
- F. Goudail, E. Lange, T. Iwamoto, K. Kyuma, N. Otsu Face recognition system using local autocorrelations and multiscale integration IEEE Trans. Pattern Anal. Mach. Intell., 18 (10) (1996), pp. 1024–1028
- M. Kreutz, B. Völpel, H. Janssen Scale-invariant image recognition based on higher order autocorrelation features Pattern Recognition, 29 (1) (1996), pp. 19–26
- T. Kurita, S. Hayamizu, Gesture recognition using HLAC features of PARCOR images and HMM based recognizer, in: Proceedings of the International Conference on Automatic Face and Gesture Recognition, 1998, pp. 422–427.
- K.Sung and T.Poggio, “Example-based learning for view-based human face detection,” tech. rep., A.I. Memo1521, CBCL Paper 112, 1994.
- H.A.Rowley, S.Baluja, and T.Kanade, “Human face detection in visual scenes,” tech. rep., CMU-CS-95-158R,1995.
- H.A.Rowley, S.Baluja, and T.Kanade, “Rotation invariant neural network-based face detection,” tech. rep., CMU-CS-97-201, 1997.
- T. Toyoda,O. Hasegawa, ”Extension of higher order local autocorrelation features”Pattern RecognitionVolume 40, Issue 5, May 2007, Pages 1466–1473
- B.Moghaddam and A.Pentland, “Probabilistic visual learning for object representation,” IEEE Trans. on PatternAnalysis and Machine Intelligence 19(7), 1997.
- L.Massone, G.Sandini, and V.Tagliasco, “Form-invariant: Topological mapping strategy for 2d shape recognition,”Computer Vision, Graphics and Image Processing 30, pp. 169–188, 1985.
- P.Kumar, P.Vadakkepat, L.Poh, “Hand Posture And Face Recognition using a Fuzzy-rough approach” International Journal of Humanoid Robotics Vol. 7, No. 3 (2010) 331–356
- P.K.Pisharady, P.Vadakkepat, A.P.Loh, “Attention based detection and recognition of hand postures against complex backgrounds”, Int.J.Comput.Vis.101 (3) (2013)403–419.
Index Terms
Keywords