The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLII-2/W4
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W4, 73–77, 2017
https://doi.org/10.5194/isprs-archives-XLII-2-W4-73-2017
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W4, 73–77, 2017
https://doi.org/10.5194/isprs-archives-XLII-2-W4-73-2017

  10 May 2017

10 May 2017

AN ALGORITHM FOR PEDESTRIAN DETECTION IN MULTISPECTRAL IMAGE SEQUENCES

V. V. Kniaz1,2 and V. V. Fedorenko1 V. V. Kniaz and V. V. Fedorenko
  • 1State Res. Institute of Aviation Systems (GosNIIAS), Moscow, Russia
  • 2Moscow Institute of Physics and Technology (MIPT), Russia

Keywords: pedestrian detection, optical flow, thermal vision, mobile robots

Abstract. The growing interest for self-driving cars provides a demand for scene understanding and obstacle detection algorithms. One of the most challenging problems in this field is the problem of pedestrian detection. Main difficulties arise from a diverse appearances of pedestrians. Poor visibility conditions such as fog and low light conditions also significantly decrease the quality of pedestrian detection. This paper presents a new optical flow based algorithm BipedDetet that provides robust pedestrian detection on a single-borad computer. The algorithm is based on the idea of simplified Kalman filtering suitable for realization on modern single-board computers. To detect a pedestrian a synthetic optical flow of the scene without pedestrians is generated using slanted-plane model. The estimate of a real optical flow is generated using a multispectral image sequence. The difference of the synthetic optical flow and the real optical flow provides the optical flow induced by pedestrians. The final detection of pedestrians is done by the segmentation of the difference of optical flows. To evaluate the BipedDetect algorithm a multispectral dataset was collected using a mobile robot.