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DCCO :
DCCO : Towards Deformable Continuous Convolution Operators for Visual Tracking
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- Johnander, Joakim (author)
- Linköpings universitet,Datorseende,Tekniska fakulteten
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- Danelljan, Martin, 1989- (author)
- Linköpings universitet,Datorseende,Tekniska fakulteten
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- Khan, Fahad Shahbaz, 1983- (author)
- Linköpings universitet,Datorseende,Tekniska fakulteten
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- Felsberg, Michael, 1974- (author)
- Linköpings universitet,Datorseende,Tekniska fakulteten
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(creator_code:org_t)
- 2017-07-28
- 2017
- English.
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In: Computer Analysis of Images and Patterns. - Cham : Springer. - 9783319646886 - 9783319646893 ; , s. 55-67
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Abstract
Subject headings
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- Discriminative Correlation Filter (DCF) based methods have shown competitive performance on tracking benchmarks in recent years. Generally, DCF based trackers learn a rigid appearance model of the target. However, this reliance on a single rigid appearance model is insufficient in situations where the target undergoes non-rigid transformations. In this paper, we propose a unified formulation for learning a deformable convolution filter. In our framework, the deformable filter is represented as a linear combination of sub-filters. Both the sub-filter coefficients and their relative locations are inferred jointly in our formulation. Experiments are performed on three challenging tracking benchmarks: OTB-2015, TempleColor and VOT2016. Our approach improves the baseline method, leading to performance comparable to state-of-the-art.
Subject headings
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datorseende och robotik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Vision and Robotics (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datorteknik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Engineering (hsv//eng)
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- kon (subject category)
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