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A novel motion detection method using 3d discrete wavelet transform

Yousefi, S ; Sharif University of Technology | 2019

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  1. Type of Document: Article
  2. DOI: 10.1109/TCSVT.2018.2885211
  3. Publisher: Institute of Electrical and Electronics Engineers Inc , 2019
  4. Abstract:
  5. The problem of motion detection has received considerable attention due to the explosive growth of its applications in video analysis and surveillance systems. While the previous approaches can produce good results, the accurate detection of motion remains a challenging task due to the difficulties raised by illumination variations, occlusion, camouflage, sudden motions appearing in burst, dynamic texture, and environmental changes such as weather conditions, sunlight changes during a day, and so on. In this paper, a novel per-pixel motion descriptor is proposed for motion detection in video sequences which outperforms the current methods in the literature particularly in severe scenarios. The proposed descriptor is based on two complementary three-dimensional discrete wavelet transforms (3D-DWT) and a 3D wavelet leader. In this approach, a feature vector is extracted for each pixel by applying a novel 3D wavelet-based motion descriptor. Then, the extracted features are clustered by the well-known K-means algorithm. The experimental results demonstrate the effectiveness of the proposed method compared to the state-of-the-art approaches in several public benchmark datasets. The application of the proposed method and additional experimental results for several challenging datasets are available online. © 1991-2012 IEEE
  6. Keywords:
  7. 3D-discrete wavelet transform ; Dynamic texture ; Motion detection ; Dynamics ; Explosives detection ; Feature extraction ; K-means clustering ; Motion analysis ; Pixels ; Security systems ; Signal detection ; Signal reconstruction ; Textures ; Video recording ; Dynamic textures ; Illumination variation ; Motion detection ; State-of-the-art approach ; Surveillance systems ; Three dimensional discrete Wavelet Transform (3D DWT) ; Video sequences ; Wavelet leader ; Discrete wavelet transforms
  8. Source: IEEE Transactions on Circuits and Systems for Video Technology ; Volume 29, Issue 12 , 2019 , Pages 3487-3500 ; 10518215 (ISSN)
  9. URL: https://ieeexplore.ieee.org/document/8561242