Volume 34 #1

Contents

1. The rates of evolution of songs and speciation in grasshoppers from subfamily Gomphocerinae (Orthoptera, Acrididae, Gomphocerinae)
2. Disruptive song – an effective mechanism to prevent copulation in stink-bugs Pentatoma rufipes
3. The role of acoustic and vibration signals in host-parasitoid unteraction in Tachinidae (Diptera) and stink-bugs (Pentatomidae)
4. Fine structure of receptive fields of orientation-selective ganglion cells in goldfish retina
5. On optimal visualization of images on photoemission displays with significant dispersion of efficiency of individual elements
6. Vanishing point detection for monocular camera extrinsic calibration under translation movement
7. A linear regression method robust to extreme stationary clutter
8. Filtering erroneous frame-by-frame results for planar rectangular objects localization in a video using matching transform graph
9. Fast filtering and back projection for CT image reconstruction
10. 1-point RANSAC for axial rotation angle estimation by tomographic projections

In this paper we introduce a method for dynamic evaluation of pitch and yaw angles of a camera mounted on mobile unmanned vehicles (MUV). The proposed method is based on vanishing point detection from a single image under motion parallel to linear objects (buildings’ edges, road markup) located in the field of view. We demonstrated that rotation angles estimation mean absolute error for our method is 0.65°, which is comparable with state of the art dynamic extrinsic calibration methods. We conducted additional research for method applicability based on data recorded from a selfdriving car, which uses road markup for self-localization. It was shown that rotation angles evaluation error of 0.65° reduces localization accuracy by 0.01 m with a route length of about 70 m, which is acceptable for most applications.

Key words: dynamic calibration, extrinsic camera calibration, vanishing point, mobile unmanned vehicles, selfdriving car

DOI: 10.31857/S0235009220010023

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