• Journal of Korea Society of Digital Industry and Information Management
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• v.14 no.2
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• pp.35-47
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• 2018

The 4th industrial revolution, digital image technology has developed beyond the limit of multimedia industry to advanced IT fusion and composite industry. Particularly, application technology related to HCI element algorithm in 3D image object recognition field is actively developed. 3D image object recognition technology evolved into intelligent image sensing and recognition technology through 3D modeling. In particular, image recognition technology has been actively studied in image processing using object recognition recognition processing, face recognition, object recognition, and 3D object recognition. In this paper, we propose a research method of human factor 3D image recognition technology applying human factor algorithm for 3D object recognition. 1. Methods of 3D object recognition using 3D modeling, image system analysis, design and human cognitive technology analysis 2. We propose a 3D object recognition parameter estimation method using FACS algorithm and optimal object recognition measurement method. In this paper, we propose a method to effectively evaluate psychological research techniques using 3D image objects. We studied the 3D 3D recognition and applied the result to the object recognition element to extract and study the characteristic points of the recognition technology.

• Journal of Korea Society of Digital Industry and Information Management
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• v.11 no.3
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• pp.99-112
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• 2015

Digital imaging technology has advanced beyond the limits of the multimedia industry IT convergence, and to develop a complex industry, particularly in the field of object recognition, face smart-phones associated with various Application technology are being actively researched. Recently, face recognition technology is evolving into an intelligent object recognition through image recognition technology, detection technology, the detection object recognition through image recognition processing techniques applied technology is applied to the IP camera through the 3D image object recognition technology Face Recognition been actively studied. In this paper, we first look at the essential human factor, technical factors and trends about the technology of the human object recognition based SPFACS(Smile Progress Facial Action Coding System)study measures the smile detection technology recognizes multi-faceted object recognition. Study Method: 1)Human cognitive skills necessary to analyze the 3D object imaging system was designed. 2)3D object recognition, face detection parameter identification and optimal measurement method using the AAM algorithm inside the proposals and 3)Face recognition objects (Face recognition Technology) to apply the result to the recognition of the person's teeth area detecting expression recognition demonstrated by the effect of extracting the feature points.

• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.3
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• pp.15-28
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• 2019

Artificial intelligence is evolving rapidly in the ICT field, smart convergence media system and content industry through the fourth industrial revolution, and it is evolving very rapidly through Big Data. In this paper, we propose a face recognition method based on object recognition based on object recognition through artificial intelligence. In this method, Were experimented and studied through the object recognition technique of artificial intelligence. In the conventional 3D image field, general research on object recognition has been carried out variously, and researches have been conducted on the side effects of visual fatigue and dizziness through 3D image. However, in this study, we tried to solve the problem caused by the quantitative difference between object recognition and object recognition for human factor algorithm that measure visual fatigue through cognitive function, morphological analysis and object recognition. Especially, The new method of computer interaction is presented and the results are shown through experiments.

• Journal of Korea Society of Digital Industry and Information Management
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• v.12 no.4
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• pp.1-12
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• 2016

Digital imaging technology has developed into a state-of-the-art IT convergence, composite industry beyond the limits of the multimedia industry, especially in the field of smart object recognition, face - Application developed various techniques have been actively studied in conjunction with the phone. Recently, face recognition technology through the object recognition technology and evolved into intelligent video detection recognition technology, image recognition technology object detection recognition process applies to skills through is applied to the IP camera, the image object recognition technology with face recognition and active research have. In this paper, we first propose the necessary technical elements of the human factor technology trends and look at the human object recognition based spFACS (Smile Progress Facial Action Coding System) for detecting smiles study plan of the image recognition technology recognizes objects. Study scheme 1). ASM algorithm. By suggesting ways to effectively evaluate psychological research skills through the image object 2). By applying the result via the face recognition object to the tooth area it is detected in accordance with the recognized facial expression recognition of a person demonstrated the effect of extracting the feature points.

• Biomolecules & Therapeutics
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• v.16 no.3
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• pp.173-178
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• 2008

Several lines of evidence indicate that scopolamine as a nonselective muscarinic antagonist disrupts object recognition performance and spatial working memory when administered systemically. In the present study, we investigated the different effects of scopolamine on acquisition, consolidation, and retrieval phases of object recognition performance and spatial working memory using the object recognition and the Morris water maze tasks in mice. In the acquisition phase test, scopolamine decreased recognition index on object recognition task and the trial 1 to trial 2 differences on Morris water maze task. In the consolidation and retrieval phase tests, scopolamine also decreased recognition index on object recognition task, where as scopolamine did not exhibited any effects on the Morris water maze task.

• International Journal of Advanced Culture Technology
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• v.7 no.4
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• pp.229-235
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• 2019

Due to the development of video and optical technology today, video equipments are being used in a variety of fields such as identification, security maintenance, and factory automation systems that generate products. In this paper, we investigate an algorithm that effectively recognizes an experimental object in an input image with a partial problem due to the mechanical problem of the input imaging device. The object recognition algorithm proposed in this paper moves and rotates the vertices constituting the outline of the experimental object to the positions of the respective vertices constituting the outline of the DB model. Then, the discordance values between the moved and rotated experimental object and the corresponding DB model are calculated, and the minimum discordance value is selected. This minimum value is the final discordance value between the experimental object and the corresponding DB model, and the DB model with the minimum discordance value is selected as the recognition result for the experimental object. The proposed object recognition method obtains satisfactory recognition results using only partial information of the experimental object.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.12
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• pp.1027-1038
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• 2005

Object recognition in the field of robotics generally has depended on a computer vision system. Recently, RFID(Radio Frequency IDentification) has been suggested as technology that supports object recognition. This paper, introduces the advanced RFID-based recognition using a novel tag which is named a 3D tag. The 3D tag was designed to facilitate object recognition. The proposed RFID system not only detects the existence of an object, but also estimates the orientation and position of the object. These characteristics allow the robot to reduce considerably its dependence on other sensors for object recognition. In this paper, we analyze the characteristics of the 3D tag-based RFID system. In addition, the estimation methods of position and orientation using the system are discussed.

• International Journal of Advanced Culture Technology
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• v.7 no.3
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• pp.134-142
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• 2019

As the 4th industry has been widely distributed, there is a need for a process of real-time image recognition in various fields such as identification of company employees, security maintenance, and development of military weapons. Therefore, in this paper, we will propose an algorithm that effectively recognizes a test object by comparing it with the DB model. The proposed object recognition system first expresses the outline of the test object as a set of vertices with the distances of predefined length or more. Then, the degree of matching of the structures of the two objects is calculated by examining the distances to the outline of the DB model from the vertices constituting the test object. Because the proposed recognition algorithm uses the outline of the object, the recognition process is easy to understand, simple to implement, and a satisfactory recognition result is obtained.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.223-228
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• 2009

We propose an on-line machine learning approach for object recognition, where new images are continuously added and the recognition decision is made without delay. Random forest (RF) classifier has been extensively used as a generative model for classification and regression applications. We extend this technique for the task of building incremental component-based detector. First we employ object descriptor model based on bag of covariance matrices, to represent an object region then run our on-line RF learner to select object descriptors and to learn an object classifier. Experiments of the object recognition are provided to verify the effectiveness of the proposed approach. Results demonstrate that the propose model yields in object recognition performance comparable to the benchmark standard RF, AdaBoost, and SVM classifiers.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.536-537
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• 2018

A goal of this paper is doing fine grained recognition of breed of animal from pet images. Research about fine grained recognition from images is continuously developing, but it is not for animal object recognition because they have polymorphism. This paper proposes method of higher animal object recognition using Grab-cut algorithm for object segmentation and Fisher Vector for image encoding.