Abstract:An approach for accelerometer based virtual digit feature extraction and recognition is proposed. Firstly, accelerations are projected on three planes respectively. Secondly, the rotation feature of the handwriting is extracted and coded. Then, normalized edit distance is used to measure the difference between different rotation feature codes. Finally, based on the rotation feature and edit distance, an algorithm of virtual handwriting digit recognition is given. Compared with time-domain feature, peak-valley feature and FFT feature, the proposed approach is effective.
[1] Bao L,Intille S S.Activity Recognition from User-Annotated Acceleration Data // Proc of the 2nd International Conference on Pervasive Computing.Vienna,Austria,2004: 1-17 [2] Thomas S,Benjamin P,Niels H,et al.Gesture Recognition with a Wii Controller // Proc of the 2nd International Conference on Tangible and Embedded Interaction.New York,USA,2008: 11-14 [3] Ermers M,Prkk J,Mntyjrvi J,et al.Detection of Daily Activities and Sports with Wearable Sensors in Controlled and Uncontrolled Conditions.IEEE Trans on Information Technology in Biomedicine,2008,12(1): 20-26 [4] Wu Jiahui,Pan Gang,Zhang Daqing,et al.Gesture Recognition with a 3-D Accelerometer // Proc of the 6th International Conference on Ubiquitous Intelligence and Computing.Brisbane,Australia,2009: 25-38 [5] Amstutz R,Oliver A,French B,et al.Performance Analysis of an HMM-Based Gesture Recognition Using a Wristwatch Device // Proc of the International Conference on Computational Science and Engineering.Vancouver,Canada,2009: 303-309 [6] Choi E S,Bang W C,Cho S J,et al.Beatbox Music Phone: Gesture-Based Interactive Mobilephone Usinga Tri-axis Accelerometer // Proc of the IEEE International Conference on Industrial Technology.HongKong,China,2005: 97-102 [7] Maguire D,Frisby R.Comparison of Feature Classification Algorithms for Activity Recognition Based on Accelerometer and Heart Rate Data // Proc of the 9th IT T Conference.Dublin,Ireland,2009: 1-8 [8] He Zhenyu,Jin Lianwen.Activity Recognition from Acceleration Data Based on Discrete Cosine Transform and SVM // Proc of the IEEE International Conference on Systems,Man and Cybernetics.San Antonio,USA,2009: 5186-5189 [9] Mntyl V M,Mntyjrvi J,Seppnnen T,et al.Hand Gesture Recognition of a Mobile Device User // Proc of the IEEE International Conference on Multimedia and Expo.New York,USA,2000,Ⅰ: 281-284 [10] He Zhenyu,Jin Lianwen,Zhen Lixin,et al.Gesture Recognition Based on 3D Accelerometer for Cell Phones // Proc of the IEEE Asia Pacific Conference on Circuits and Systems.Macao,China,2008: 217-220 [11] Zhang Xu,Chen Xiang,Wang Wenhui,et al.Hand Gesture Recognition and Virtual Game Control Based on 3D Accelerometer and EMG Sensors // Proc of the 14th International Conference on Intelligent User Interfaces.Sanibel Island,USA,2009: 401-406 [12] Cho S J,Choi E S,Bang W C,et al.Two-Stage Recognition of Raw Acceleration Signals for 3-D Gesture-Understanding Cell Phones // Proc of the 10th International Workshop on Frontiers in Handwriting Recognition.Nijmegen,Netherlands,2006: 3854-3859 [13] Levenshtein V I.Binary Codes Capable of Correcting Deletions,Insertions,and Reversals.Soviet Physics Doklady,1966,10(8): 707-710 [14] Vapnik V N.The Nature of Statistical Learning Theory.New York,USA: Springer Press,1999