Algorithm performance measurement method and device

Abstract

The invention provides an algorithm performance measurement method and device. The method comprises the following steps: determining a tracking system algorithm to be evaluated; obtaining one or moreparameters of the tracking system algorithm for tracking the target object in a video; wherein the one or more parameters are used for comprehensively measuring a tracking system algorithm with stepsof measuring the stability and accuracy of the tracking system algorithm, solving the problem that the performance evaluation scheme for the target tracking system algorithm is not comprehensive enough in the prior art, and completely and objectively measuring the performance of the target tracking system algorithm.

Description

technical field

[0001] This application relates to but is not limited to the field of electronic tracking, and specifically relates to a method and device for measuring the performance of an algorithm. Background technique

[0002] In the related art, the mean-square error (Mean-Squre Error, MSE for short) is more common among target tracking evaluation methods. MSE refers to the expected difference between the true value and the estimated value. In fact, since expectations are usually hard to obtain, it is very difficult to directly calculate the MSE index. Therefore, a metric that is often used is the root mean square error RMSE, which uses sampled values ​​from MonteCarlo simulations to statistically approximate this expected value. RMSE is the most commonly used indicator in the field of multi-target tracking. However, the RMSE indicator has several shortcomings: first, it is not a concept of distance in Euclidean space; second, when the number of targets is large, suc...

Examples

Embodiment 1

[0019] The method embodiment provided in Embodiment 1 of this application can be executed in a computer terminal or a similar computing device. Take running on a computer terminal as an example, figure 1 It is a block diagram of the hardware structure of the computer terminal of a method for measuring the performance of an algorithm in the embodiment of the present application, such as figure 1 As shown, the computer terminal 10 may include one or more ( figure 1 Only one is shown in the figure) a processor 102 (the processor 102 may include but not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA) and a memory 104 for storing data. Optionally, the above-mentioned computer terminal also Transmission means 106 for communication functions as well as input and output devices 108 may be included. Those of ordinary skill in the art can understand that, figure 1 The shown structure is only for illustration, and does not limit the str...

Embodiment 2

[0050] In this embodiment, a device for measuring the performance of an algorithm is also provided, and the device is used to implement the above embodiments and preferred implementation modes, and what has already been described will not be repeated. As used below, the term "module" may be a combination of software and / or hardware that realizes a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, implementations in hardware, or a combination of software and hardware are also possible and contemplated.

[0051] Figure 4 is a structural block diagram of the performance measuring device of the algorithm according to the embodiment of the present application, such as Figure 4 As shown, the device includes:

[0052] The first acquisition module 42 is configured to acquire the predicted data of the target object's action trajectory predicted by the first algorithm and the real data of the target object's a...

Embodiment 3

[0060] The embodiment of the present application also provides a storage medium. Optionally, in this embodiment, the above-mentioned storage medium may be configured to store program codes for performing the following steps:

[0061] S1, for the video stream data, acquire the predicted data of the target object’s action trajectory predicted by the first algorithm and the real data of the target object’s action trajectory, wherein the first algorithm is used to track the target object ;

[0062] S2. Obtain at least one of the following parameters according to the predicted data and the real data: average difference, the mean value of position differences of multiple frame data of the video stream data, wherein the position difference of each frame data is the difference between the predicted position and the real position; the first value, the number of real data that does not correspond to the predicted data; the second value, the number of predicted data that does not corres...

technical field

[0001] This application relates to but is not limited to the field of electronic tracking, and specifically relates to a method and device for measuring the performance of an algorithm. Background technique

[0002] In the related art, the mean-square error (Mean-Squre Error, MSE for short) is more common among target tracking evaluation methods. MSE refers to the expected difference between the true value and the estimated value. In fact, since expectations are usually hard to obtain, it is very difficult to directly calculate the MSE index. Therefore, a metric that is often used is the root mean square error RMSE, which uses sampled values ​​from MonteCarlo simulations to statistically approximate this expected value. RMSE is the most commonly used indicator in the field of multi-target tracking. However, the RMSE indicator has several shortcomings: first, it is not a concept of distance in Euclidean space; second, when the number of targets is large, suc...

Examples

Embodiment 1

[0019] The method embodiment provided in Embodiment 1 of this application can be executed in a computer terminal or a similar computing device. Take running on a computer terminal as an example, figure 1 It is a block diagram of the hardware structure of the computer terminal of a method for measuring the performance of an algorithm in the embodiment of the present application, such as figure 1 As shown, the computer terminal 10 may include one or more ( figure 1 Only one is shown in the figure) a processor 102 (the processor 102 may include but not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA) and a memory 104 for storing data. Optionally, the above-mentioned computer terminal also Transmission means 106 for communication functions as well as input and output devices 108 may be included. Those of ordinary skill in the art can understand that, figure 1 The shown structure is only for illustration, and does not limit the str...

Embodiment 2

[0050] In this embodiment, a device for measuring the performance of an algorithm is also provided, and the device is used to implement the above embodiments and preferred implementation modes, and what has already been described will not be repeated. As used below, the term "module" may be a combination of software and / or hardware that realizes a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, implementations in hardware, or a combination of software and hardware are also possible and contemplated.

[0051] Figure 4 is a structural block diagram of the performance measuring device of the algorithm according to the embodiment of the present application, such as Figure 4 As shown, the device includes:

[0052] The first acquisition module 42 is configured to acquire the predicted data of the target object's action trajectory predicted by the first algorithm and the real data of the target object's a...

Embodiment 3

[0060] The embodiment of the present application also provides a storage medium. Optionally, in this embodiment, the above-mentioned storage medium may be configured to store program codes for performing the following steps:

[0061] S1, for the video stream data, acquire the predicted data of the target object’s action trajectory predicted by the first algorithm and the real data of the target object’s action trajectory, wherein the first algorithm is used to track the target object ;

[0062] S2. Obtain at least one of the following parameters according to the predicted data and the real data: average difference, the mean value of position differences of multiple frame data of the video stream data, wherein the position difference of each frame data is the difference between the predicted position and the real position; the first value, the number of real data that does not correspond to the predicted data; the second value, the number of predicted data that does not corres...

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