Motion Segmentation Using Spectral Clustering on Indian Road Scenes
| Autor: | Sarthak Upadhyay, Shanti Medasani, Mahtab Sandhu, K. Madhava Krishna |
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| Rok vydání: | 2019 |
| Předmět: |
0209 industrial biotechnology
business.industry Computer science ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 02 engineering and technology Frame rate Object detection Spectral clustering 020901 industrial engineering & automation Computer Science::Computer Vision and Pattern Recognition 0202 electrical engineering electronic engineering information engineering Graph (abstract data type) 020201 artificial intelligence & image processing Segmentation Computer vision Artificial intelligence business ComputingMethodologies_COMPUTERGRAPHICS |
| Zdroj: | Lecture Notes in Computer Science ISBN: 9783030110208 ECCV Workshops (5) |
| Popis: | We propose a novel motion segmentation formulation over spatio-temporal depth images obtained from stereo sequences that segments multiple motion models in the scene in an unsupervised manner. The motion segmentation is obtained at frame rates that compete with the speed of the stereo depth computation. This is possible due to a decoupling framework that first delineates spatial clusters and subsequently assigns motion labels to each of these cluster with analysis of a novel motion graph model. A principled computation of the weights of the motion graph that signifies the relative shear and stretch between possible clusters lends itself to a high fidelity segmentation of the motion models in the scene. |
| Databáze: | OpenAIRE |
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