Redirigiendo al acceso original de articulo en 20 segundos...
ARTÍCULO
TITULO

A neural network approach for occlusion detection in video

Maxim Velikanov    
Alexandra Anzina    
Sergey Lavrushkin    
Dmitry Vatolin    

Resumen

Occlusions are a set of pixels, which are visible in a single frame of two sequential frames in a video. Finding occlusions is of great importance in the field of computer vision. Precise detection of occlusions will improve the accuracy of many video processing methods, such as: frame interpolation, optical flow calculation, color propagation etc. The majority of existing methods are based on optimization of an energy function, which is computationally expensive. It is also worth noting that accurate estimation of occlusions is hard with no information about movement between frames, and knowledge of occlusions during optical flow estimation allows the algorithm to avoid wrong correspondences between pixels of frames. Taking this into consideration we present a novel method of occlusion detection based on PWC-net, an optical flow calculation algorithm. The key idea is to construct a pyramid of features with different resolutions for frame processing. This way of processing originates from a common computer graphics technique and is widely adopted. We also performed a comparison of our method with 15 similar methods on the MPI-Sintel dataset.

 Artículos similares

       
 
Pengyun Chen, Zhiru Li, Guangqing Liu, Ziyi Wang, Jiayu Chen, Shangyao Shi, Jian Shen and Lizhou Li    
The positioning results of terrain matching in flat terrain areas will significantly deteriorate due to the influence of terrain nonlinearity and multibeam measurement noise. To tackle this problem, this study presents the Pulse-Coupled Neural Network (P... ver más

 
Pengfei Ning, Dianjun Zhang, Xuefeng Zhang, Jianhui Zhang, Yulong Liu, Xiaoyi Jiang and Yansheng Zhang    
The Array for Real-time Geostrophic Oceanography (Argo) program provides valuable data for maritime research and rescue operations. This paper is based on Argo historical and satellite observations, and inverted sea surface and submarine drift trajectori... ver más

 
Min Xu, Wenjie Tian and Xiangpeng Zhang    
The three-degrees-of-freedom (3-DOF) parallel robot is commonly employed as a shipborne stabilized platform for real-time compensation of ship disturbances. Pose accuracy is one of its most critical performance indicators. Currently, neural networks have... ver más

 
Shun Wang, Jiayan Wang, Zhikang Xu, Ji Wang, Rui Li and Jinliang Dai    
The application of titanium alloy in shipbuilding can reduce ship weight and carbon emissions. To solve the problem of titanium alloy forming, the deformation prediction of titanium alloy line heating based on a backpropagation (BP) neural network and sp... ver más

 
Yifan Shang, Wanneng Yu, Guangmiao Zeng, Huihui Li and Yuegao Wu    
Image recognition is vital for intelligent ships? autonomous navigation. However, traditional methods often fail to accurately identify maritime objects? spatial positions, especially under electromagnetic silence. We introduce the StereoYOLO method, an ... ver más