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Performance analysis of vehicle detection based on spatial saliency and local image features in H.265 (HEVC) 4K video for developing a relationship between iou and subjective evaluation value
Author(s) -
Aktar Most Shelina,
Horita Yuukou
Publication year - 2020
Publication title -
ieej transactions on electrical and electronic engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.254
H-Index - 30
eISSN - 1931-4981
pISSN - 1931-4973
DOI - 10.1002/tee.23089
Subject(s) - artificial intelligence , computer science , computer vision , kadir–brady saliency detector , computation , salient , pattern recognition (psychology) , saliency map , feature (linguistics) , image (mathematics) , scale invariant feature transform , construct (python library) , algorithm , linguistics , philosophy , programming language
A vehicle detection method fusing spatial saliency and local image features is presented in this paper to analyze the detection performance in compressed domain. Most of the existing visual saliency models use the input images, in which salient objects are to be detected and are free from complex background and overlapping areas. Moreover, they are very sensitive to the complex scene and different illuminations. In this method, the Scale Invariant Feature Transform and Harris features in combination with spatial saliency model play an important role in detecting vehicles from the scene. A one‐to‐one symmetric search is performed on the descriptors to select a set of matched interest point pairs for vehicle detection. We use 4K video of a road scene with different types of vehicles. The proposed method is able to detect desired overlapping objects from the road scene without heavy computation like other training‐based methods. In addition, the detection performance is analyzed in a H.265 compressed domain to help construct a relationship between objective and subjective evaluation value. The performance of this method is demonstrated by the experimental results. © 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.