Cooking Behavior Recognition Using Egocentric Vision for Cooking Navigation

2017 ◽  
Vol 29 (4) ◽  
pp. 728-736 ◽  
Author(s):  
Sho Ooi ◽  
Tsuyoshi Ikegaya ◽  
Mutsuo Sano ◽  
◽  
Keyword(s):  
Navigation System ◽  
Recognition Rate ◽  
Line Of Sight ◽  
Recognition Method ◽  
Behavior Recognition ◽  
System A ◽  
Arm Motions ◽  
Average Recognition Rate ◽  
Egocentric Vision ◽  
Cooking Utensil

This paper presents a cooking behavior recognition method for achievement of a cooking navigation system. A cooking navigation system is a system that recognizes the progress of a user in cooking, and accordingly presents an appropriate recipe, thus supporting the activity. In other words, an appropriate recognition of cooking behaviors is required. Among the various cooking behavior recognition methods, such as the use of context with the object being focused on and use of information in the line of sight, we have so far attempted cooking behavior recognition using a method that focuses on the motion of arms. Using the cooking behavior rate obtained from the motion of arms and cooking utensils, this study achieves recognition of the cooking behavior. The average recognition rate was 63% when calculated by the conventional method of focusing on arm motions. It has been improved by approximately 20% by adding the proposed cooking utensil information and optimizing the parameters. An average recognition rate of 84% was achieved with respect to the five types of basic behaviors of “cut,” “peel,” “stir,” “add,” and “beat,” indicating the effectiveness of the proposed method.

Stressed Speech Recognition Method Based on Difference Subspace Combined with Dynamic Time Warping

2012 ◽  
Vol 241-244 ◽  
pp. 1640-1646
Author(s):  
Cheng Guo Lv ◽  
Ru Bo Zhang ◽  
Pei Hua Li
Keyword(s):  
Dynamic Time Warping ◽  
Recognition Rate ◽  
Decision Criterion ◽  
Time Warping ◽  
Training Set ◽  
Recognition Method ◽  
Average Recognition Rate ◽  
Normal Environment ◽  
Acceleration Of Gravity ◽  
Dynamic Time

Speech under G-force which produced when speaker was under different acceleration of gravity was analyzed and researched, considered as principal part and stressed part to research. An isolated word recognition approach was proposed which combined difference subspace means with dynamic time warping technique. The method recognized speech under G-force by constructing a difference subspace to remove the stressed part. Dynamic time warping technique was adopted to make all feature vectors of one word in the training set have equal length, and a corresponding decision criterion was suggested. For a small vocabulary including 15 words, the method obtained the average recognition rate of 98.3%, which almost equal to the rate in normal environment. The method not only worked well in normal conditions but also had good performance for speech under G-force.

A Smart Recognition Method for Otological Drill Milling through a Bone Tissue Wall

2014 ◽  
Vol 571-572 ◽  
pp. 331-338
Author(s):  
Xi Sheng Li ◽  
Yong Ming Xie ◽  
Zhi Qiang Gao ◽  
Guo Dong Feng
Keyword(s):  
Bone Tissue ◽  
Information Fusion ◽  
Recognition Rate ◽  
Fusion Method ◽  
Recognition Method ◽  
Ear Surgery ◽  
Minimally Invasive Operation ◽  
Average Recognition Rate ◽  
Sensor Information ◽  
Medical Equipments

Surgeons are striving to achieve higher quality results in minimally invasive operation. Intelligent medical equipments are able to improve operation safety. Otological drill milling through a bone tissue wall is a common milling fault in ear surgery. In this paper a multi-sensor information fusion method for identifying milling faults is presented. Five surgeons experimented on calvarian bones using the intelligent otological drill. The average recognition rate of milling faults was 91%, and only 0.8% of normal millings were identified as milling faults.

GESTURE RECOGNITION SYSTEM FOR NIGERIAN TRIBAL GREETING POSTURES USING SUPPORT VECTOR MACHINE

2020 ◽  
Vol 5 (2) ◽  
pp. 609
Author(s):  
Segun Aina ◽  
Kofoworola V. Sholesi ◽  
Aderonke R. Lawal ◽  
Samuel D. Okegbile ◽  
Adeniran I. Oluwaranti
Keyword(s):  
Support Vector Machine ◽  
Gesture Recognition ◽  
Recognition Rate ◽  
Recognition Task ◽  
Recognition System ◽  
Human Interaction ◽  
Support Vector ◽  
System A ◽  
Extraction Algorithm ◽  
Gaussian Blur

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.

Machine-Printed Invoice Number Based on Fuzzy Recognition

2012 ◽  
Vol 214 ◽  
pp. 705-710 ◽  
Author(s):  
Xiao Ping Xian
Keyword(s):  
Neural Network ◽  
Bp Neural Network ◽  
Recognition Rate ◽  
Real System ◽  
Recognition Method ◽  
Recognition Time ◽  
Recognition Ability ◽  
System Requirements ◽  
Fuzzy Recognition ◽  
Detection And Separation

A new fuzzy recognition method of machine-printed invoice number based on neural network is presented. This method includes ten links: invoice number detection and separation of right on top of invoice, binarization, denoising, incline correction, extraction of invoice code numerals, window scaling, location standardization, thinning, extraction of numeral feature and fuzzy recognition based on BP neural network. Through testing, the recognition rate of this method can be over 99%.The recognition time of characters for character is less than 1 second, which means that the method is of more effective recognition ability and can better satisfy the real system requirements.

scholarly journals An on-chip imaging droplet-sorting system: a real-time shape recognition method to screen target cells in droplets with single cell resolution

2017 ◽  
Vol 7 (1) ◽  
Author(s):  
Mathias Girault ◽  
Hyonchol Kim ◽  
Hisayuki Arakawa ◽  
Kenji Matsuura ◽  
Masao Odaka ◽  
...  
Keyword(s):  
Single Cell ◽  
Real Time ◽  
Shape Recognition ◽  
Target Cells ◽  
Recognition Method ◽  
System A ◽  
Time Shape ◽  
Droplet Sorting ◽  
On Chip ◽  
Sorting System

scholarly journals A Practical Method for the Automatic Recognition of Rock Structures in Panoramic Borehole Image during Deep-Hole Drilling Engineering

2021 ◽  
Vol 11 (21) ◽  
pp. 10490
Author(s):  
Xianjian Zou ◽  
Chuanying Wang ◽  
Huajun Zhang ◽  
Shuangyuan Chen
Keyword(s):  
Recognition Rate ◽  
Automatic Recognition ◽  
Characteristic Functions ◽  
Hole Drilling ◽  
Time Cost ◽  
Recognition Method ◽  
Structural Plane ◽  
Drilling Engineering ◽  
Borehole Image ◽  
Borehole Imaging

Digital panoramic borehole imaging technology has been widely used in the practice of drilling engineering. Based on many high-definition panoramic borehole images obtained by the borehole imaging system, this paper puts forward an automatic recognition method based on clustering and characteristic functions to perform intelligent analysis and automatic interpretation researches, and successfully applied to the analysis of the borehole images obtained at the Wudongde Hydropower Station in the south-west of China. The results show that the automatic recognition method can fully and quickly automatically identify most of the important structural planes and their position, dip, dip angle and gap width and other characteristic parameter information in the entire borehole image. The recognition rate of the main structural plane is about 90%. The accuracy rate is about 85%, the total time cost is about 3 h, and the accuracy deviation is less than 4% among the 12 boreholes with a depth of about 50 m. The application of automatic recognition technology to the panoramic borehole image can greatly improve work efficiency, reduce the time cost, and avoid the interference caused by humans, making it possible to automatically recognize the structural plane parameters of the full-hole image.

scholarly journals Flexible Rope Manipulation Using Elastic Deformation Modeling by Dual Manipulator System with Vision Sensor

2004 ◽  
Vol 16 (1) ◽  
pp. 31-38 ◽  
Author(s):  
Takayuki Matsuno ◽  
◽  
Toshio Fukuda ◽  
Fumihito Arai ◽  
Yasuhisa Hasegawa ◽  
...  
Keyword(s):  
Object Recognition ◽  
Elastic Deformation ◽  
Object Manipulation ◽  
Object Model ◽  
Vision Sensor ◽  
Recognition Method ◽  
Simple Task ◽  
System A

In this paper we propose a flexible object manipulation method by a dual manipulator system. A flexible object such a rope and paper is easily deformed and has hysteresis. Various approaches have been made on the research for the flexible object manipulation. However in the former research works, the manipulator system works only simple task. For more complex works with flexible object, the robot has to hand over the flexible object. So, we propose a flexible object recognition method which can hand over a flexible object using vision information and flexible object model. The dual manipulator system tied a cylinder object with flexible rope by repeating handing over actions in the experiment.

scholarly journals Practical Recognition System for Text Printed on Clear Reflected Material

2012 ◽  
Vol 2012 ◽  
pp. 1-16 ◽  
Author(s):  
Khader Mohammad ◽  
Sos Agaian
Keyword(s):  
Processing Time ◽  
Recognition Rate ◽  
Recognition System ◽  
Experimental Results ◽  
Research Fields ◽  
Average Recognition Rate ◽  
Clear Plastic ◽  
Novel Methods ◽  
Processor Speed ◽  
Background Contrast

Text embedded in an image contains useful information for applications in the medical, industrial, commercial, and research fields. While many systems have been designed to correctly identify text in images, no work addressing the recognition of degraded text on clear plastic has been found. This paper posits novel methods and an apparatus for extracting text from an image with the practical assumption: (a) poor background contrast, (b) white, curved, and/or differing fonts or character width between sets of images, (c) dotted text printed on curved reflective material, and/or (d) touching characters. Methods were evaluated using a total of 100 unique test images containing a variety of texts captured from water bottles. These tests averaged a processing time of ~10 seconds (using MATLAB R2008A on an HP 8510 W with 4 G of RAM and 2.3 GHz of processor speed), and experimental results yielded an average recognition rate of 90 to 93% using customized systems generated by the proposed development.

scholarly journals Navigated Placement of Two Odontoid Screws Using the O-Arm Navigation System: A Technical Case Report

Cureus ◽  
2020 ◽  
Author(s):  
Clara K Starkweather ◽  
Ramin A Morshed ◽  
Caleb Rutledge ◽  
Phiroz Tarapore
Keyword(s):  
Case Report ◽  
Navigation System ◽  
System A

Research on Adaptive Face Gender Recognition Based on Compressive Sensing

2014 ◽  
Vol 989-994 ◽  
pp. 4187-4190 ◽  
Author(s):  
Lin Zhang
Keyword(s):  
Feature Extraction ◽  
Compressive Sensing ◽  
Recognition Accuracy ◽  
Recognition Rate ◽  
Low Frequency ◽  
Face Image ◽  
Gender Recognition ◽  
Recognition Method ◽  
Frequency Information ◽  
Learning Machine

An adaptive gender recognition method is proposed in this paper. At first, do multiwavlet transform to face image and get its low frequency information, then do feature extraction to the low frequency information using compressive sensing (CS), use extreme learning machine (ELM) to achieve gender recognition finally. In the process of feature extraction, we use genetic algorithm (GA) to get the number of measurements of CS in order to gain the highest recognition rate, so the method can adaptive access optimal performance. Experimental results show that compared with PDA and LDA, the new method improved the recognition accuracy substantially.

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