• Journal of Electrical Engineering and Technology
• /
• v.13 no.2
• /
• pp.961-968
• /
• 2018

Recently, researches on automatic recognition of human activities have been actively carried out with the emergence of various intelligent systems. Since a large amount of visual data can be secured through Closed Circuit Television, it is required to recognize human behavior in a dynamic situation rather than a static situation. In this paper, we propose new intelligent human activity recognition model using the trajectory information extracted from the video sequence. The proposed model consists of three steps: segmentation and partitioning of trajectory step, feature extraction step, and behavioral learning step. First, the entire trajectory is fuzzy partitioned according to the motion characteristics, and then temporal features and spatial features are extracted. Using the extracted features, four pedestrian behaviors were modeled by decision tree learning algorithm and performance evaluation was performed. The experiments in this paper were conducted using Caviar data sets. Experimental results show that trajectory provides good activity recognition accuracy by extracting instantaneous property and distinctive regional property.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.8 no.4
• /
• pp.248-253
• /
• 2008

In this paper, a novel vehicle detection algorithm is proposed that utilizes the color histogram of the image. The color histogram is used to search the image for regions with shadow, block symmetry, and block non-homogeneity, thereby detecting the vehicle region. First, an integral histogram of the input image is computed to decrease the amount of required computation time for the block color histograms. Then, shadow detection is performed and the block symmetry and block non-homogeneity are checked in a cascade manner to detect the vehicle in the image. Finally, the proposed scheme is applied to both still images taken in a parking lot and an on-road video sequence to demonstrate its effectiveness.

• Proceedings of the KIEE Conference
• /
• 1998.07g
• /
• pp.2427-2429
• /
• 1998

Digital watermarking is the techinque which embeds the invisible signal into multimedia data such as audio, video, images, for copyright protection, including owner identification and copy control information. This paper proposes a new watermark embedding and extraction technique by extending the direct sequence spread spectrum technique. The proposed technique approximates the frequency component of pixels in spatial domain by using Laplacian mask and adaptively embeds the watermark considering the HVS to reduce the degradation of Image. In watermark extraction process, the proposed technique strengthens the high frequency components of image and extracts the watermark by demodulation. All this processes are performed in spatial domain to reduce the processing time.

• Proceedings of the KIEE Conference
• /
• 2000.07d
• /
• pp.3041-3043
• /
• 2000

GUI(graphical user interface) has been the dominant platform for HCI(human computer interaction). The GUI-based style of interaction has made computers simpler and easier to use. However GUI will not easily support the range of interaction necessary to meet users' needs that are natural, intuitive, and adaptive. In this paper we study an approach to track a hand in an image sequence and recognize it, in each video frame for replacing the mouse as a pointing device to virtual reality. An algorithm for real time processing is proposed by estimating of the position of the hand and segmentation, considering the orientation of motion and color distribution of hand region.

• Proceedings of the Optical Society of Korea Conference
• /
• 2008.07a
• /
• pp.119-120
• /
• 2008

A HMD type multi-focus 3D display system is developed and proof about satisfaction of eye accommodation is tested. Four LEDs(Light Emitting Diode) and a DMD are used to generate four parallax images at single eye and any mechanical part is not included in this system. The multi-focus means the ability of monocular depth cue to various depth levels. By achieving multi-focus function, we developed a 3D display system for only one eye, which can satisfy the accommodation to displayed virtual objects within defined depth. We could achieve a result that focus adjustment is possible at 5 step depths in sequence within 2m depth for only one eye. Additionally, the change level of burring depending on the focusing depth is tested by captured photos and moving pictures of video camera and several subjects. And the HMD type multi-focus 3D display can be applied to a monocular 3D display and monocular AR 3D display.

• Journal of Korean Institute of Industrial Engineers
• /
• v.21 no.2
• /
• pp.239-254
• /
• 1995

Automated Storage/Retrieval (AS/R) systems have been used mostly in manufacturing or distribution industry in order to store or retrieve palletized items automatically. Since the items ore heavy or bulky, only one pallet at a time is moved by the stacker crane In this study, however, we introduce the "multi -load" AS/R system in which the items to be stored are data storage devices of equal size such as video tape or compact disc. Since the items are small and light multiple items can be stored and retrieved in each trip by using a magazine and a robot arm mounted on the crane Given the magazine capacity, and the locations of retrieval items and empty cells in the rack, the throughput of the multi-load AS/R system will depend on the selection of storage locations and the sequence of visits. We propose four heuristic algorithms for the multi-command. Computer simulation is used to evaluate the four algorithms in terms of throughput and number of back tracking of the crane.

• Proceedings of the Korean Information Science Society Conference
• /
• 2005.07b
• /
• pp.865-867
• /
• 2005

비디오 데이터의 장면전환 검출은 동영상 검색, 색인 등의 응용을 위한 첫 단계로서 매우 중요한 기술이다. 본 논문에서는 점진적 장면전환의 하나인 wipe 장면전환의 검출 방법을 제안한다. 제안하는 방법은 wipe 구간 내에서 현재 장면과 이전 장면의 경계선의 이동 궤적을 이용하여 wipe 장면전환을 검출하는 기존의 방법에 허프 변환을 추가하는 것을 기반으로 한다. 이 방법은 보다 정확한 wipe 경계선의 이동 궤적을 구함으로써 기존의 방법에 비해 보다 높은 검출 성능을 보여준다.

• Analytical Science and Technology
• /
• v.17 no.4
• /
• pp.315-321
• /
• 2004

The aim of this study was to investigate the evidential value of blue and black ballpoint pens on paper by nondestructive techniques. In this work, 21 blue and 22 black ballpoint pens which were purchased on different brands were analyzed by Raman Spectroscopy and Video Spectral Comparator (VSC). Surface-Enhanced Resonance Raman Spectroscopy (SERRS) with excitation at 685 nm and VSC with several spot light filters were used for the discrimination of ballpoint pen inks. In the SERR spectra, the ballpoint pen inks on paper could be shown sharp spectral bands and distinguished by their band shapes and relative intensities. In the blue and black ballpoint pen inks, the discriminating powers (DP) by SERRS were 0.85 and 0.67 and the DP by VSC were 0.88 and 0.90, respectively. The DP by combined sequence of techniques was all 0.97 in both black and blue ballpoint pen inks.

• Smart Media Journal
• /
• v.5 no.1
• /
• pp.78-87
• /
• 2016

The major problems of recent object tracking methods are related to the inefficient detection of moving objects due to occlusions, noisy background and inconsistent body motion. This paper presents a robust method for the detection and tracking of a moving in infrared animal videos. The tracking system is based on adaptive optical flow generation, Gaussian mixture and Kalman filtering. The adaptive Gaussian model of optical flow (GMOF) is used to extract foreground and noises are removed based on the object motion. Kalman filter enables the prediction of the object position in the presence of partial occlusions, and changes the size of the animal detected automatically along the image sequence. The presented method is evaluated in various environments of unstable background because of winds, and illuminations changes. The results show that our approach is more robust to background noises and performs better than previous methods.

• Journal of Korea Multimedia Society
• /
• v.12 no.12
• /
• pp.1728-1735
• /
• 2009

Human action tracking plays an important place in human-computer-interaction, human action tracking is a challenging task because of the exponentially increased computational complexity in terms of the degrees of freedom of the object and the severe image ambiguities incurred by frequent self-occlusions. In this paper, we will propose a novel method to track human action, in our technique, a dynamic background estimation algorithm will be applied firstly. Based on the estimated background, we then extract the human object from the video sequence, and the skeletonization method and Hough transform method will be used to detect the main structure of human body and each part rotation angle. The calculated rotation angles will be used to control a crane in the port, thus we can just control the container crane by using signalman body. And the experimental results can show that our proposed method can get a preferable result than the conventional methods such as: MIT, JPF or MFMC.