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Real-Time Feature Matching in Image Sequences for Non-Structured Environments. Applications to Vehicle Guidance

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Abstract

This paper describes an integrated vehicle control system with visual feedback. A general-purpose, low-level feature matching method, able to work in real time without any strict assumptions on the environment structure or camera parameters, generates low-level matching results, which are used as source of data for applications like mobile object tracking, among others. A generalized predictive path-tracking control approach keeps the vehicle on the trajectory defined by the moving target. In the low-level matching process, block-based features (windows) are selected and tracked along a stream of monocular images; least residual square error and similarity between clusters of features are used as constraints to select the right matching pair between multiple candidates. Real-time performance is achieved through optimized algorithms and a parallel DSP-based multiprocessor system implementation. Object detection and tracking is motion-based, and does not require a predefined model of the target. The integrated control system has been tested on the ROMEO-3R experimental vehicle.

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Ferruz, J., Ollero, A. Real-Time Feature Matching in Image Sequences for Non-Structured Environments. Applications to Vehicle Guidance. Journal of Intelligent and Robotic Systems 28, 85–123 (2000). https://doi.org/10.1023/A:1008163332131

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