Object tracking system implementation method based on Cortex system multi-core processor

A multi-core processor and target tracking technology, applied in the field of target tracking, can solve problems such as the inability to take into account the operation and management of system peripherals, the difficulty of increasing the main frequency of the system, and the complex structure of the operating bus, achieving good flexibility and scalability, real-time accuracy Tracking, good adaptability effect

Inactive Publication Date: 2017-12-01
XIDIAN UNIV
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Problems solved by technology

The embedded operating platform based on the FPGA soft core has unique parallel execution capabilities, but the realization of its parallel interface is still a big technical problem; researchers have not been able to solve the problem of quickly converting serial algorithms into parallel algorithms, especially When some algorithms must be executed according to the serial process, the shortcomings are more prominent; in addition, the soft core itself in the embedded operating platform based on the FPGA

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  • Object tracking system implementation method based on Cortex system multi-core processor
  • Object tracking system implementation method based on Cortex system multi-core processor
  • Object tracking system implementation method based on Cortex system multi-core processor

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Embodiment Construction

[0066] The present invention will be described in further detail below in conjunction with specific examples, but the embodiments of the present invention are not limited thereto.

[0067] refer to figure 1 , the specific steps of the overall system process of the present invention are as follows:

[0068] Step 1, obtaining video sequence material;

[0069] This system uses the Parrot drone to obtain the video material needed for the experiment, which is convenient for expanding the system and applying it to real-time target tracking systems based on drones.

[0070] Step 1a, install the APP software (official AR.FreeFlight) for operating the drone on the Android phone or IOS phone, and ensure sufficient storage space (2G is appropriate) on the phone to prepare for storing videos;

[0071] Step 1b, start the drone, control the flight of the drone through the mobile phone, adjust its flight attitude, and use the shooting function of the drone to obtain the video of the ground...

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Abstract

The invention relates to an object tracking system implementation method based on a Cortex system multi-core processor. The method includes the following steps: acquiring a video; programming to implement a target tracking algorithm based on SURF registration and KALMAN prediction; performing program porting cross operation systems; establishing an embedded system basic platform which is implemented by the target tracking algorithm; implementing cross-hardware porting of a PC terminal with the target tracking algorithm; and realizing the cooperative work between the ARM core and a DSP core inside a panda board. According to the invention, the system herein operates the target tracking algorithm on independent single-board device, which eliminates the reliance on the PC terminal of traditional image algorithm, realizes embedded image processing, makes the algorithm more flexible and expandable, and provides a much easier and more flexible interface for the follow up unmanned aerial plane tracking platform; and in a more complex moving background, can real-time and accurately tracking a moving object.

Description

technical field [0001] The invention belongs to the technical field of target tracking, and in particular relates to a method for realizing a target tracking system based on a Cortex series multi-core processor. Background technique [0002] Video target tracking is a cutting-edge research topic in the field of computer vision today, and it is widely used in many fields such as intelligent transportation, security monitoring, military applications, and human-computer interaction. Therefore, the realization of embedded video image processing system will also become the focus of researchers, which has important academic significance and practical value. [0003] In terms of moving object tracking, the existing tracking methods are mainly divided into five categories: area tracking, edge tracking, feature tracking, model tracking, and hybrid tracking. Classical algorithms mainly include optical flow method, mean shift, particle filter, feature point tracking, etc. The optical...

Claims

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Application Information

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IPC IPC(8): G06T7/277G06T7/246
CPCG06T2200/28
Inventor 朱娟娟许金利张恩泽李海军李诚
Owner XIDIAN UNIV
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