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Multi-target vehicle tracking method based on MDP

A target vehicle, vehicle tracking technology, applied in instruments, character and pattern recognition, computer parts and other directions, can solve problems such as poor tracking effect

Pending Publication Date: 2020-07-03
NANJING INGO ARTIFICIAL INTELLIGENCE RES INST CO LTD
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  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is to propose an online multi-target tracking algorithm based on MDP, which solves the main technical difficulties faced by vehicle tracking technology and the problem of poor tracking effect

Method used

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  • Multi-target vehicle tracking method based on MDP
  • Multi-target vehicle tracking method based on MDP
  • Multi-target vehicle tracking method based on MDP

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Embodiment Construction

[0066] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided for more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0067] The embodiment of the present invention provides a kind of MDP-based multi-target vehicle tracking method, referring to Figure 1-2 shown, including:

[0068] S1. Acquiring a target vehicle through a video sequence, detecting the target vehicle, and the target vehicle enters an active state; wherein, the state of the target vehicle includes: an active state, a tracking state, an inactive state and a lost state;

[0069] S2....

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Abstract

The invention discloses a multi-target vehicle tracking method based on a Markov decision process (MDP), and the method comprises the steps: obtaining a target vehicle through a video sequence, detecting the target vehicle, and enabling the target vehicle to enter an activated state; wherein the state of the target vehicle comprises an activated state, a tracking state, a non-activated state and alost state; for the target vehicle in the activated state, training a binary classifier in an offline mode, and judging the state transition of the target vehicle according to the binary classifier;for the target vehicle entering the tracking state, an appearance template is constructed for the target vehicle in an online mode, and state transition of the target vehicle is judged according to the appearance template; for a target vehicle in a lost state, judgment of state transition of the target vehicle is realized through data association binary classifier reinforcement learning; the method can overcome the main technical difficulties faced by the vehicle tracking technology, reduce the tracking error probability and improve the tracking effect.

Description

technical field [0001] The invention relates to the technical field of target tracking, in particular to an MDP-based multi-target vehicle tracking method. Background technique [0002] According to the characteristics of the input video sequence when the target tracking algorithm is running, the input data can be divided into fixed camera shooting data and moving camera shooting data. For the data captured by a fixed camera, the background of the shooting scene is almost unchanged because the shooting point is fixed, and the most obvious change in the entire input data is the target to be tracked, so this type of data has lower requirements on the algorithm. As for the data captured by the motion camera, because the shooting point is moving all the time, this causes the entire shooting picture to be in constant motion, which poses a great challenge to the correct operation of the tracking algorithm. At the same time, environmental factors will pose more challenges to vehic...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06K9/00
CPCG06V20/42G06V2201/08G06V2201/07G06F18/24G06F18/214
Inventor 庄文芹袁柱柱
Owner NANJING INGO ARTIFICIAL INTELLIGENCE RES INST CO LTD
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