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Träfflista för sökning "(WFRF:(Danelljan Martin)) srt2:(2014)"

Sökning: (WFRF:(Danelljan Martin)) > (2014)

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1.
  • Danelljan, Martin, et al. (författare)
  • Accurate Scale Estimation for Robust Visual Tracking
  • 2014
  • Ingår i: Proceedings of the British Machine Vision Conference 2014. - : BMVA Press. - 1901725529
  • Konferensbidrag (refereegranskat)abstract
    • Robust scale estimation is a challenging problem in visual object tracking. Most existing methods fail to handle large scale variations in complex image sequences. This paper presents a novel approach for robust scale estimation in a tracking-by-detection framework. The proposed approach works by learning discriminative correlation filters based on a scale pyramid representation. We learn separate filters for translation and scale estimation, and show that this improves the performance compared to an exhaustive scale search. Our scale estimation approach is generic as it can be incorporated into any tracking method with no inherent scale estimation.Experiments are performed on 28 benchmark sequences with significant scale variations. Our results show that the proposed approach significantly improves the performance by 18.8 % in median distance precision compared to our baseline. Finally, we provide both quantitative and qualitative comparison of our approach with state-of-the-art trackers in literature. The proposed method is shown to outperform the best existing tracker by 16.6 % in median distance precision, while operating at real-time.
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2.
  • Danelljan, Martin, et al. (författare)
  • Adaptive Color Attributes for Real-Time Visual Tracking
  • 2014
  • Ingår i: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2014. - : IEEE Computer Society. - 9781479951178 ; , s. 1090-1097
  • Konferensbidrag (refereegranskat)abstract
    • Visual tracking is a challenging problem in computer vision. Most state-of-the-art visual trackers either rely on luminance information or use simple color representations for image description. Contrary to visual tracking, for object recognition and detection, sophisticated color features when combined with luminance have shown to provide excellent performance. Due to the complexity of the tracking problem, the desired color feature should be computationally efficient, and possess a certain amount of photometric invariance while maintaining high discriminative power.This paper investigates the contribution of color in a tracking-by-detection framework. Our results suggest that color attributes provides superior performance for visual tracking. We further propose an adaptive low-dimensional variant of color attributes. Both quantitative and attributebased evaluations are performed on 41 challenging benchmark color sequences. The proposed approach improves the baseline intensity-based tracker by 24% in median distance precision. Furthermore, we show that our approach outperforms state-of-the-art tracking methods while running at more than 100 frames per second.
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  • Resultat 1-2 av 2
Typ av publikation
konferensbidrag (2)
Typ av innehåll
refereegranskat (2)
Författare/redaktör
Felsberg, Michael (2)
Danelljan, Martin (2)
Khan, Fahad (1)
van de Weijer, Joost (1)
Häger, Gustav (1)
Shahbaz Khan, Fahad (1)
Lärosäte
Linköpings universitet (2)
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Engelska (2)
Forskningsämne (UKÄ/SCB)
Naturvetenskap (2)
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2014 (2)Ta bort avgränsningen

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