• Title/Summary/Keyword: frame detection

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Convolutional GRU and Attention based Fall Detection Integrating with Human Body Keypoints and DensePose

  • Yi Zheng;Cunyi Liao;Ruifeng Xiao;Qiang He
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.18 no.9
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    • pp.2782-2804
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    • 2024
  • The integration of artificial intelligence technology with medicine has rapidly evolved, with increasing demands for quality of life. However, falls remain a significant risk leading to severe injuries and fatalities, especially among the elderly. Therefore, the development and application of computer vision-based fall detection technologies have become increasingly important. In this paper, firstly, the keypoint detection algorithm ViTPose++ is used to obtain the coordinates of human body keypoints from the camera images. Human skeletal feature maps are generated from this keypoint coordinate information. Meanwhile, human dense feature maps are produced based on the DensePose algorithm. Then, these two types of feature maps are confused as dual-channel inputs for the model. The convolutional gated recurrent unit is introduced to extract the frame-to-frame relevance in the process of falling. To further integrate features across three dimensions (spatio-temporal-channel), a dual-channel fall detection algorithm based on video streams is proposed by combining the Convolutional Block Attention Module (CBAM) with the ConvGRU. Finally, experiments on the public UR Fall Detection Dataset demonstrate that the improved ConvGRU-CBAM achieves an F1 score of 92.86% and an AUC of 95.34%.

A Voltage Disturbance Detection Method for Computer Application Loads (컴퓨터 응용 부하들을 위한 전압 외란 검출 방법)

  • 최재호
    • Proceedings of the KIPE Conference
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    • 2000.07a
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    • pp.245-248
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    • 2000
  • In this paper a novel method for voltage disturbance detection is presented. This is a instantaneous detection method using normalized error get in synchronous reference frame and also it is implemented in digital. Feedback noise the problem of digital implementation is removed by a digital filter of which the time delay is compensated through numerical analysis.

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Frame Rate Up-Conversion with Occlusion Detection Function (폐색영역탐지 기능을 갖는 프레임율 변환)

  • Kim, Nam-Uk;Lee, Yung-Lyul
    • Journal of Broadcast Engineering
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    • v.20 no.2
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    • pp.265-272
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    • 2015
  • A new technology on video frame rate up-conversion (FRUC) is presented by combining the median filter and motion estimation (ME) with an occlusion detection (OD) method. First, ME is performed to have a motion vector. Then, the OD method is used to refine motion vector in the occlusion region. Since the wrong motion vector can be obtained with high possibility in the occluded area, a median filtering that less depends on the motion vector is applied to that area, and since the motion vector is continuous and robust in the non-occluded area, BDMC(Bi-Directional Motion Compensated interpolation) is applied to obtain interpolated image in that area. BDMC using the bi-directional motion vectors achieves good results when continuity and robustness of the motion vector is higher. Experimental results show that the proposed algorithm provides better performance than the conventional approach. The average gain of PSNR (Peak Signal to Noise Ratio) is approximately 0.16 dB in the test sequences compared with BDMC.

Gradual scene change detection using Cut frame difference and Dynamic threshold (동적 임계값과 컷 프레임 차를 이용한 점진적 전환 검출 기법)

  • Yeum, Sun-Ju;Kim, Woo-Saeng
    • The KIPS Transactions:PartB
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    • v.9B no.3
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    • pp.293-302
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    • 2002
  • Gradual scene change detection is known as more difficult problem then abrupt scene change detection on video data analysis for contents based retrieval. In this paper, we present a new method for scene change detection far both abrupt and gradual change using the variable dynamic threshold arid cut frame difference (CFD). For this, We present the characteristics arid mathematical models of gradual transitions anti then, how can be detected by the CFD. And also we present new scene change detection algorithm based on cut frame difference. By the experimental result using real world video data indicate that the proposed method detect various scene changes both abrupt and gradual change efficiently without time-consuming computation and any dependency on a kind of gradual change effects.

Smoke Detection Method of Color Image Using Object Block Ternary Pattern (물체 블록의 삼진 패턴을 이용한 컬러 영상의 연기 검출 방법)

  • Lee, Yong-Hun;Kim, Won-Ho
    • Journal of Satellite, Information and Communications
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    • v.9 no.4
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    • pp.1-6
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    • 2014
  • Color image processing based on smoke detection is suitable detecting target to early detection of fire smoke. A method for detecting the smoke is processed in the pre-processing movement and color. And Next, characteristics of smoke such as diffusion, texture, shape, and directionality are used to post-processing. In this paper, propose the detection method of density distribution characteristic in characteristics of smoke. the generate a candidate regions by color thresholding image in Detecting the movement of smoke to the 10Frame interval and accumulated while 1second image. then check whether the pattern of the smoke by candidate regions to applying OBTP(Object Block Ternary Pattern). every processing is Block-based processing, moving detection is decided the candidate regions of the moving object by applying an adaptive threshold to frame difference image. The decided candidate region accumulates one second and apply the threshold condition of the smoke color. make the ternary pattern compare the center block value with block value of 16 position in each candidate region of the smoke, and determine the smoke by compare the candidate ternary pattern and smoke ternary pattern.

A Fast Motion Detection and Tracking Algorithm for Automatic Control of an Object Tracking Camera (객체 추적 카메라 제어를 위한 고속의 움직임 검출 및 추적 알고리즘)

  • 강동구;나종범
    • Journal of Broadcast Engineering
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    • v.7 no.2
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    • pp.181-191
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    • 2002
  • Video based surveillance systems based on an active camera require a fast algorithm for real time detection and tracking of local motion in the presence of global motion. This paper presents a new fast and efficient motion detection and tracking algorithm using the displaced frame difference (DFD). In the Proposed algorithm, first, a Previous frame is adaptively selected according to the magnitude of object motion, and the global motion is estimated by using only a few confident matching blocks for a fast and accurate result. Then, a DFD is obtained between the current frame and the selected previous frame displaced by the global motion. Finally, a moving object is extracted from the noisy DFD by utilizing the correlation between the DFD and current frame. We implement this algorithm into an active camera system including a pan-tilt unit and a standard PC equipped with an AMD 800MHz processor. The system can perform the exhaustive search for a search range of 120, and achieve the processing speed of about 50 frames/sec for video sequences of 320$\times$240. Thereby, it provides satisfactory tracking results.

Synergetics based damage detection of frame structures using piezoceramic patches

  • Hong, Xiaobin;Ruan, Jiaobiao;Liu, Guixiong;Wang, Tao;Li, Youyong;Song, Gangbing
    • Smart Structures and Systems
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    • v.17 no.2
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    • pp.167-194
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    • 2016
  • This paper investigates the Synergetics based Damage Detection Method (SDDM) for frame structures by using surface-bonded PZT (Lead Zirconate Titanate) patches. After analyzing the mechanism of pattern recognition from Synergetics, the operating framework with cooperation-competition-update process of SDDM was proposed. First, the dynamic identification equation of structural conditions was established and the adjoint vector (AV) set of original vector (OV) set was obtained by Generalized Inverse Matrix (GIM).Then, the order parameter equation and its evolution process were deduced through the strict mathematics ratiocination. Moreover, in order to complete online structural condition update feature, the iterative update algorithm was presented. Subsequently, the pathway in which SDDM was realized through the modified Synergetic Neural Network (SNN) was introduced and its assessment indices were confirmed. Finally, the experimental platform with a two-story frame structure was set up. The performances of the proposed methodology were tested for damage identifications by loosening various screw nuts group scenarios. The experiments were conducted in different damage degrees, the disturbance environment and the noisy environment, respectively. The results show the feasibility of SDDM using piezoceramic sensors and actuators, and demonstrate a strong ability of anti-disturbance and anti-noise in frame structure applications. This proposed approach can be extended to the similar structures for damage identification.

Anti-islanding Detection Method for BESS Based on 3 Phase Inverter Using Negative-Sequence Current Injection (역상분 전류 주입을 적용한 3상 인버터 기반 BESS의 단독 운전 검출 방법)

  • Sin, Eun-Suk;Kim, Hyun-Jun;Han, Byung-Moon
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.64 no.9
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    • pp.1315-1322
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    • 2015
  • This paper proposes an active islanding detection method for the BESS (Battery Energy Storage System) with 3-phase inverter which is connected to the AC grid. The proposed method adopts the DDSRF (Decoupled Double Synchronous Reference Frame) PLL (Phase Locked-Loop) so that the independent control of positive-sequence and negative-sequence current is successfully carried out using the detected phase angle information. The islanding state can be detected by sensing the variation of negative-sequence voltage at the PCC (Point of Common Connection) due to the injection of 2-3% negative-sequence current from the BESS. The proposed method provides a secure and rapid detection under the variation of negative-sequence voltage due to the sag and swell. The feasibility of proposed method was verified by computer simulations with PSCAD/EMTDC and experimental analyses with 5kW hardware prototype for the benchmark circuit of islanding detection suggested by IEEE 1547 and UL1741. The proposed method would be applicable for the secure detection of islanding state in the grid-tied Microgrid.

Comparison Speed of Pedestrian Detection with Parallel Processing Graphic Processor and General Purpose Processor (병렬처리 그래픽 프로세서와 범용 프로세서에서의 보행자 검출 처리 속도 비교)

  • Park, Jang-Sik
    • The Journal of the Korea institute of electronic communication sciences
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    • v.10 no.2
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    • pp.239-246
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    • 2015
  • Video based object detection is basic technology of implementing smart CCTV system. Various features and algorithms are developed to detect object, however computations of them increase with the performance. In this paper, performances of object detection algorithms with GPU and CPU are compared. Adaboost and SVM algorithm which are widely used to detect pedestrian detection are implemented with CPU and GPU, and speeds of detection processing are compared for the same video. As results of frame rate comparison of Adaboost and SVM algorithm, it is shown that the frame rate with GPU is faster than CPU.

Shot Change Detection Using Fuzzy Clustering Method on MPEG Video Frames (퍼지 클러스터링 기법을 이용한 MPEG 비디오의 장면 전환 검출)

  • Lim, Seong-Jae;Kim, Woon;Lee, Bae-Ho
    • Proceedings of the IEEK Conference
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    • 2000.11d
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    • pp.159-162
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    • 2000
  • In this paper, we propose an efficient method to detect shot changes in compressed MPEG video data by using reference features among video frames. The reference features among video frames imply the similarities among adjacent frames by prediction coded type of each frame. A shot change is detected if the similarity degrees of a frame and its adjacent frames are low. And the shot change detection algorithm is improved by using Fuzzy c-means (FCM) clustering algorithm. The FCM clustering algorithm uses the shot change probabilities evaluated in the mask matching of reference ratios and difference measure values based on frame reference ratios.

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