• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.12 no.4
• /
• pp.1897-1903
• /
• 2011

This paper discusses a 2D/3D conversion of images using technologies like object extraction and depth-map creation. The general procedure for converting 2D images into a 3D image is extracting objects from 2D image, recognizing the distance of each points, generating the 3D image and correcting the image to generate with less noise. This paper proposes modified new methods creating a depth-map from 2D image and recognizing the distance of objects in it. Depth-map information which determines the distance of objects is the key data creating a 3D image from 2D images. To get more accurate depth-map data, noise filtering is applied to the optical flow. With the proposed method, better depth-map information is calculated and better 3D image is constructed.

• Management Science and Financial Engineering
• /
• v.3 no.1
• /
• pp.15-38
• /
• 1997

In a flexible manufacturing system, a cell controller is able to identify and evaluate a number of alternative decisions to meet the objectives set by the factory level controller. In this paper, a Petri net-based cell controller is presented to accomplish this task. A static model is developed by using the Integrated Computer Aided Definition(IDEF0) method to represent clear functional relationships among the objects of the system. Based on the static model, two Petri net models are developed for the physical part flow and for the information flow. Multiple decision alternatives are generated from the physical part flow model and are synchronized with the information flow model for execution of the selected alternative.

• Journal of Convergence for Information Technology
• /
• v.11 no.11
• /
• pp.38-43
• /
• 2021

As the number of augmented reality games using augmented reality technology increases, the demands of users are also increasing. Game technologies used in augmented reality games are mainly games using MARKER, MARKERLESS, GPS, etc. Games using this technology can augment the background and other objects. To solve this problem, we want to help develop augmented reality games by analyzing objects in the background, which is an important element of augmented reality. To analyze the background in the augmented reality game, the background object was analyzed by applying a deep learning model using TensorFlow Lite in the UNITY engine. Using this result, we obtained the result that augmented objects can be placed in the game according to the types of objects analyzed in the background. By utilizing this research, it will be possible to develop advanced augmented reality games by augmenting objects that fit the background.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.32B no.3
• /
• pp.48-56
• /
• 1995

This paper presents a method of implementing efficient optical flow estimation for dynamic scene analysis using the hierarchical Hopfield neural networks. Given the two consequent inages, Zhou and Chellappa suggested the Hopfield neural network for computing the optical flow. The major problem of this algorithm is that Zhou and Chellappa's network accompanies self-feedback term, which forces them to check the energy change every iteration and only to accept the case where the lower the energy level is guaranteed. This is not only undesirable but also inefficient in implementing the Hopfield network. The another problem is that this model cannot allow the exact computation of optical flow in the case that the disparities of the moving objects are large. This paper improves the Zhou and Chellapa's problems by modifying the structure of the network to satisfy the convergence condition of the Hopfield model and suggesting the hierarchical algorithm, which enables the computation of the optical flow using the hierarchical structure even in the presence of large disparities.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.13 no.2
• /
• pp.827-833
• /
• 2012

In this paper, we propose an improved optical flow algorithm which reduces computational complexity as well as noise level. This algorithm reduces computational time by applying level simplification technique and removes noise by using eigenvectors of objects. Optical flow is one of the accurate algorithms used to generate depth information from two image frames using the vectors which track the motions of pixels. This technique, however, has disadvantage of taking very long computational time because of the pixel-based calculation and can cause some noise problems. The level simplifying technique is applied to reduce the computational time, and the noise is removed by applying optical flow only to the area of having eigenvector, then using the edge image to generate the depth information of background area. Three-dimensional images were created from two-dimensional images using the proposed method which generates the depth information first and then converts into three-dimensional image using the depth information and DIBR(Depth Image Based Rendering) technique. The error rate was obtained using the SSIM(Structural SIMilarity index).

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.41 no.5
• /
• pp.23-34
• /
• 2004

In this paper we propose a feature point tracking algorithm using optical flow under non-prior taming active feature model (NPT-AFM). The proposed algorithm mainly focuses on analysis non-rigid objects[1], and provides real-time, robust tracking by NPT-AFM. NPT-AFM algorithm can be divided into two steps: (i) localization of an object-of-interest and (ii) prediction and correction of the object position by utilizing the inter-frame information. The localization step was realized by using a modified Shi-Tomasi's feature tracking algoriam[2] after motion-based segmentation. In the prediction-correction step, given feature points are continuously tracked by using optical flow method[3] and if a feature point cannot be properly tracked, temporal and spatial prediction schemes can be employed for that point until it becomes uncovered again. Feature points inside an object are estimated instead of its shape boundary, and are updated an element of the training set for AFH Experimental results, show that the proposed NPT-AFM-based algerian can robustly track non-rigid objects in real-time.

• Journal of information and communication convergence engineering
• /
• v.21 no.4
• /
• pp.329-336
• /
• 2023

This paper introduces an edge AI-based scene-specific object detection system for long-term traffic management, focusing on analyzing congestion and movement via cameras. It aims to balance fast processing and accuracy in traffic flow data analysis using edge computing. We adapt the YOLOv5 model, with four heads, to a scene-specific model that utilizes the fixed camera's scene-specific properties. This model selectively detects objects based on scale by blocking nodes, ensuring only objects of certain sizes are identified. A decision module then selects the most suitable object detector for each scene, enhancing inference speed without significant accuracy loss, as demonstrated in our experiments.

• The KIPS Transactions:PartB
• /
• v.16B no.2
• /
• pp.109-116
• /
• 2009

In this thesis, an object tracking method based on the active feature model and the optical flow in stereo images is proposed. We acquired the translation information of object of interest and the features of object by utilizing the geometric information and depth of stereo images. Tracking performance is improved for the occlude object with this information by predicting the movement information of features of the occlude object. Rigid and non-rigid objects are experimented. From the result of experiment, the OOI can be real-time tracked from complicate back ground. Besides, we got the improved result of object tracking in any occlusion state, no matter what it is rigid or non-rigid object.

• Journal of Internet Computing and Services
• /
• v.8 no.4
• /
• pp.129-136
• /
• 2007

The domain model pattern which belongs to enterprise architecture patterns has reusability, scalability and maintainability. To use the domain model pattern, mapping with persistency layer, transaction management and various services are needed. This paper proposes that relationship management service to solve a consistency error which arises in case of removing domain objects. The proposed relationship management service monitors methods of domain objects and intercepts the flow of control to solve the reference errors. This service is implemented by using AOP(Aspect-Oriented Programming), so it can provide the service without modifications of domain objects and other services.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.23 no.4
• /
• pp.787-795
• /
• 1998

In this paper, we have improved the speed of gradient operation, which needs to calculate Optical Flow for estimating a moving object, and proposed a method which estimate the contour of a moving object by the logical operationg of Optical Flow and edge in noisy images. The proposed method, which recognize to a moving ogject and traking a moving object, using logical operation of Optical Flow and edge in low-level has a advantage that is simpler than the known method for moving objects estimation. In addition, we have simulated several images using method I and method II on improved Gradient operation speed. When we have compared the average value of total operation time, method I is improved with 12% of operation speed compared with the known method, method II is improved with 38% operation speed.