Vehicle tracking method based on depth information

Abstract

The invention discloses a vehicle tracking method based on depth information. The method comprises clustering each frame of data by adoption of the method based on distance; extracting eigenvectors of targets inside clusters; initially judging whether the targets are vehicle targets according to the eigenvectors; tracking a single target by adoption of a kalman filter; realizing target association of the targets in a current frame through computing and a cost equation of the tracked target; and estimating the current state according to the current state when the targets being tracked are in leak detection state, continue tracking the targets when the targets are detected again so that coherence of tracking is maintained. The vehicle tracking method can track a new target appearing in a scanning environment and delete disappearing targets, namely, the number of the tracked targets changes along with actual conditions, and therefore the defect that only targets of definite number can be tracked when the joint probabilistic data association algorithm is adopted is overcome. Compared with the multiple hypothesis tracking algorithm, the vehicle tracking method is small both in calculated amount and memory overhead.

Description

[0001] Technical field: The present invention relates to a method in the field of pattern recognition and intelligent vehicle technology, in particular to a vehicle tracking method based on depth information for an automobile assisted driving system. Background technique: [0002] Methods for vehicle recognition and tracking mainly include machine vision-based methods and depth information-based methods. Vehicle detection systems based on machine vision generally use CCD cameras, which have low hardware costs and can perceive rich environmental information, but are greatly affected by environmental changes. The shadow of trees on sunny days, the reflection of smooth surfaces, the accumulation of water on the road, and the lack of light at night will all have a great impact on the recognition of image information. Algorithms based on depth information generally use laser radar, microwave radar, etc. to obtain depth information, which can accurately obtain the distance informati...

AI Technical Summary

Problems solved by technology

[0005] At present, the commonly used multi-target tracking method was originally developed out of the needs of military and aviation. The target targets have high mobility, complex flight paths, and large clutter interference. Therefore, the model is also relatively complex and the amount of calculation is large.

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