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Sökning: WFRF:(Chahl Javaan)

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1.
  • Kristan, Matej, et al. (författare)
  • The Sixth Visual Object Tracking VOT2018 Challenge Results
  • 2019
  • Ingår i: Computer Vision – ECCV 2018 Workshops. - Cham : Springer Publishing Company. - 9783030110086 - 9783030110093 ; , s. 3-53
  • Konferensbidrag (refereegranskat)abstract
    • The Visual Object Tracking challenge VOT2018 is the sixth annual tracker benchmarking activity organized by the VOT initiative. Results of over eighty trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in the recent years. The evaluation included the standard VOT and other popular methodologies for short-term tracking analysis and a “real-time” experiment simulating a situation where a tracker processes images as if provided by a continuously running sensor. A long-term tracking subchallenge has been introduced to the set of standard VOT sub-challenges. The new subchallenge focuses on long-term tracking properties, namely coping with target disappearance and reappearance. A new dataset has been compiled and a performance evaluation methodology that focuses on long-term tracking capabilities has been adopted. The VOT toolkit has been updated to support both standard short-term and the new long-term tracking subchallenges. Performance of the tested trackers typically by far exceeds standard baselines. The source code for most of the trackers is publicly available from the VOT page. The dataset, the evaluation kit and the results are publicly available at the challenge website (http://votchallenge.net).
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2.
  • Tao, Yiting, et al. (författare)
  • A Computer Vision Milky Way Compass
  • 2023
  • Ingår i: Applied Sciences (Switzerland). - 2076-3417. ; 13:10
  • Tidskriftsartikel (refereegranskat)abstract
    • The Milky Way is used by nocturnal flying and walking insects for maintaining heading while navigating. In this study, we have explored the feasibility of the method for machine vision systems on autonomous vehicles by measuring the visual features and characteristics of the Milky Way. We also consider the conditions under which the Milky Way is used by insects and the sensory systems that support their detection of the Milky Way. Using a combination of simulated and real Milky Way imagery, we demonstrate that appropriate computer vision methods are capable of reliably and accurately extracting the orientation of the Milky Way under an unobstructed night sky. The technique presented achieves angular accuracy of better then (Formula presented.) ° under moderate light pollution conditions but also demonstrates that higher light pollution levels will adversely effect orientation estimates by systems depending on the Milky Way for navigation.
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