Segment Matching Gesture Recognition Algorithm and its Application in Smartphone

2014 ◽  
Vol 511-512 ◽  
pp. 936-940
Author(s):  
Yi Zhang ◽  
Sheng Hui Li ◽  
Yuan Luo

Aim to the traditional acceleration gesture recognition system on PC platform had the problem of high power consumption, hard to carry and low recognition rate, the paper proposes a novel gesture recognition algorithm. The algorithm first sampled the gestures signal acceleration by acceleration sensor, and then segmented and smoothing filtered the collected original signal. After preprocessing, extracted the feature value and segmented the feature value according to segments signal energy. Finally for all the segments used the improved DTW(Dynamic Time Warping) algorithm[1] to match the extracted signal features with the predefined template feature respectively and integrated the matching results of them, then concluded the final recognition results. We apply the proposed algorithm to the smartphone and test the system. Testing result shows that: The novel algorithm can improve the recognition rate and enable the system to real-time and accuracy recognizes gestures.

2013 ◽  
Vol 5 (2) ◽  
pp. 101-104
Author(s):  
Tomyslav Sledevič ◽  
Liudas Stašionis

The paper describes the FPGA-based implementation of Lithuanian isolated word recognition algorithm. FPGA is selected for parallel process implementation using VHDL to ensure fast signal processing at low rate clock signal. Cepstrum analysis was applied to features extraction in voice. The dynamic time warping algorithm was used to compare the vectors of cepstrum coefficients. A library of 100 words features was created and stored in the internal FPGA BRAM memory. Experimental testing with speaker dependent records demonstrated the recognition rate of 94%. The recognition rate of 58% was achieved for speaker-independent records. Calculation of cepstrum coefficients lasted for 8.52 ms at 50 MHz clock, while 100 DTWs took 66.56 ms at 25 MHz clock. Article in Lithuanian. Santrauka Pateikiamas lietuvių kalbos pavienių žodžių atpažinimo algoritmo įgyvendinimas lauku programuojama logine matrica (LPLM). LPLM įrenginys pasirinktas dėl lygiagrečiai veikiančių procesų įgyvendinimo galimybės taikant VHDL kalbą. Tai užtikrina spartų signalų apdorojimą esant taktiniam dažniui iki 50 MHz. Kalbos požymiams išskirti taikoma kepstrinė šnekos analizė. Požymiams palyginti taikomas dinaminis laiko skalės kraipymo (DSLK) metodas. Sudaryta 100 žodžių požymių biblioteka, kuri saugoma vidinėje LPLM BRAM atmintyje. Pasiektas 94 % atpažinimo tikslumas priklausomai nuo kalbėtojo ir 58 % – nepriklausomai nuo kalbėtojo. Kepstro koeficientų skaičiavimas vienam žodžiui trunka 8,52 ms, esant 50 MHz taktiniam dažniui, ir šimtui DLSK – 66,56 ms, esant 25 MHz taktiniam dažniui.


2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Hyo-Rim Choi ◽  
TaeYong Kim

We propose a modified dynamic time warping (DTW) algorithm that compares gesture-position sequences based on the direction of the gestural movement. Standard DTW does not specifically consider the two-dimensional characteristic of the user’s movement. Therefore, in gesture recognition, the sequence comparison by standard DTW needs to be improved. The proposed gesture-recognition system compares the sequences of the input gesture’s position with gesture positions saved in the database and selects the most similar gesture by filtering out unrelated gestures. The suggested algorithm uses the cosine similarity of the movement direction at each moment to calculate the difference and reflects the characteristics of the gesture movement by using the ratio of the Euclidean distance and the proportional distance to the calculated difference. Selective spline interpolation assists in solving the issue of recognition-decline at instances of gestures. Through experiments with public databases (MSRC-12 and G3D), the suggested algorithm revealed an improved performance on both databases compared to other methods.


2019 ◽  
Vol 9 (3) ◽  
pp. 528 ◽  
Author(s):  
Fahn Chin-Shyurng ◽  
Shih-En Lee ◽  
Meng-Luen Wu

Gesture recognition is a human−computer interaction method, which is widely used for educational, medical, and entertainment purposes. Humans also use gestures to communicate with each other, and musical conducting uses gestures in this way. In musical conducting, conductors wave their hands to control the speed and strength of the music played. However, beginners may have a limited comprehension of the gestures and might not be able to properly follow the ensembles. Therefore, this paper proposes a real-time musical conducting gesture recognition system to help music players improve their performance. We used a single-depth camera to capture image inputs and establish a real-time dynamic gesture recognition system. The Kinect software development kit created a skeleton model by capturing the palm position. Different palm gestures were collected to develop training templates for musical conducting. The dynamic time warping algorithm was applied to recognize the different conducting gestures at various conducting speeds, thereby achieving real-time dynamic musical conducting gesture recognition. In the experiment, we used 5600 examples of three basic types of musical conducting gestures, including seven capturing angles and five performing speeds for evaluation. The experimental result showed that the average accuracy was 89.17% in 30 frames per second.


2020 ◽  
Vol 5 (2) ◽  
pp. 609
Author(s):  
Segun Aina ◽  
Kofoworola V. Sholesi ◽  
Aderonke R. Lawal ◽  
Samuel D. Okegbile ◽  
Adeniran I. Oluwaranti

This paper presents the application of Gaussian blur filters and Support Vector Machine (SVM) techniques for greeting recognition among the Yoruba tribe of Nigeria. Existing efforts have considered different recognition gestures. However, tribal greeting postures or gestures recognition for the Nigerian geographical space has not been studied before. Some cultural gestures are not correctly identified by people of the same tribe, not to mention other people from different tribes, thereby posing a challenge of misinterpretation of meaning. Also, some cultural gestures are unknown to most people outside a tribe, which could also hinder human interaction; hence there is a need to automate the recognition of Nigerian tribal greeting gestures. This work hence develops a Gaussian Blur – SVM based system capable of recognizing the Yoruba tribe greeting postures for men and women. Videos of individuals performing various greeting gestures were collected and processed into image frames. The images were resized and a Gaussian blur filter was used to remove noise from them. This research used a moment-based feature extraction algorithm to extract shape features that were passed as input to SVM. SVM is exploited and trained to perform the greeting gesture recognition task to recognize two Nigerian tribe greeting postures. To confirm the robustness of the system, 20%, 25% and 30% of the dataset acquired from the preprocessed images were used to test the system. A recognition rate of 94% could be achieved when SVM is used, as shown by the result which invariably proves that the proposed method is efficient.


Author(s):  
Aleksandra Rutkowska ◽  
Magdalena Szyszko

AbstractThis study provides an application of dynamic time warping algorithm with a new window constraint to assess consumer expectations’ information content regarding current and future inflation. Our study’s contribution is the novel application of DTW for testing expectations’ forward-lookingness. Additionally, we modify the algorithm to adjust it for a specific question on the information content of our data. The DTW overcomes constraints of the standard tool that examines forward-lookingness: DTW does not impose assumptions on time series properties. In empirical study we cover seven European counties and compare the DTW outcomes with the results of previous studies in these economies using a standard methodology. The research period covers 2001 to mid-2018. Application of DTW provides information on the degree of expectations’ forward-lookingness. The result, after standardization, are similar to the standard parameters of hybrid specification of expectations. Moreover, the rankings of most forward-looking consumers are replicated. Our results confirm the economic intuition, and they do not contradict previous studies.


2014 ◽  
Vol 687-691 ◽  
pp. 3861-3868
Author(s):  
Zheng Hong Deng ◽  
Li Tao Jiao ◽  
Li Yan Liu ◽  
Shan Shan Zhao

According to the trend of the intelligent monitoring system, on the basis of the study of gait recognition algorithm, the intelligent monitoring system is designed based on FPGA and DSP; On the one hand, FPGA’s flexibility and fast parallel processing algorithms when designing can be both used to avoid that circuit can not be modified after designed; On the other hand, the advantage of processing the digital signal of DSP is fully taken. In the feature extraction and recognition, Zernike moment is selected, at the same time the system uses the nearest neighbor classification method which is more mature and has good real-time performance. Experiments show that the system has high recognition rate.


2017 ◽  
Vol 24 (2) ◽  
pp. 17-26
Author(s):  
Mustafa Yagimli ◽  
Huseyin Kursat Tezer

Abstract The real-time voice command recognition system used for this study, aims to increase the situational awareness, therefore the safety of navigation, related especially to the close manoeuvres of warships, and the courses of commercial vessels in narrow waters. The developed system, the safety of navigation that has become especially important in precision manoeuvres, has become controllable with voice command recognition-based software. The system was observed to work with 90.6% accuracy using Mel Frequency Cepstral Coefficients (MFCC) and Dynamic Time Warping (DTW) parameters and with 85.5% accuracy using Linear Predictive Coding (LPC) and DTW parameters.


2017 ◽  
Vol 10 (13) ◽  
pp. 248
Author(s):  
John Sahaya Rani Alex ◽  
Mitali Bhojwani

Objective of this research is to implement a speech recognition algorithm in smaller form factor device. Speech recognition is an extensively used inmobile and in numerous consumer electronics devices. Dynamic time warping (DTW) method which is based on dynamic programming is chosen tobe implemented for speech recognition because of the latest trend in evolving computing power. Implementation of DTW in field-programmable gatearray is chosen for its featured flexibility, parallelization and shorter time to market. The above algorithm is implemented using Verilog on Xilinx ISE.The warping cost is less if the similarity is found and is more for dissimilar sequences which is verified in the simulation output. The results indicatethat real time implementation of DTW based speech recognition could be done in future.


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