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- Title
Exploiting temporal and spatial constraints in traffic sign detection from a moving vehicle.
- Authors
Šegvić, Siniša; Brkić, Karla; Kalafatić, Zoran; Pinz, Axel
- Abstract
This paper addresses detection, tracking and recognition of traffic signs in video. Previous research has shown that very good detection recalls can be obtained by state-of-the-art detection algorithms. Unfortunately, satisfactory precision and localization accuracy are more difficultly achieved. We follow the intuitive notion that it should be easier to accurately detect an object from an image sequence than from a single image. We propose a novel two-stage technique which achieves improved detection results by applying temporal and spatial constraints to the occurrences of traffic signs in video. The first stage produces well-aligned temporally consistent detection tracks by managing many competing track hypotheses at once. The second stage improves the precision by filtering the detection tracks by a learned discriminative model. The two stages have been evaluated in extensive experiments performed on videos acquired from a moving vehicle. The obtained experimental results clearly confirm the advantages of the proposed technique.
- Subjects
VIDEO recording; OBJECT tracking (Computer vision); SUPERVISED learning; TRAFFIC signs &; signals; AUTOMATION
- Publication
Machine Vision & Applications, 2014, Vol 25, Issue 3, p649
- ISSN
0932-8092
- Publication type
Article
- DOI
10.1007/s00138-011-0396-y