New Performance Measures for Object Tracking under Complex Environments

11/13/2021
by   Ajoy Mondal, et al.
0

Various performance measures based on the ground truth and without ground truth exist to evaluate the quality of a developed tracking algorithm. The existing popular measures - average center location error (ACLE) and average tracking accuracy (ATA) based on ground truth, may sometimes create confusion to quantify the quality of a developed algorithm for tracking an object under some complex environments (e.g., scaled or oriented or both scaled and oriented object). In this article, we propose three new auxiliary performance measures based on ground truth information to evaluate the quality of a developed tracking algorithm under such complex environments. Moreover, one performance measure is developed by combining both two existing measures ACLE and ATA and three new proposed measures for better quantifying the developed tracking algorithm under such complex conditions. Some examples and experimental results conclude that the proposed measure is better than existing measures to quantify one developed algorithm for tracking objects under such complex environments.

READ FULL TEXT

page 16

page 17

page 18

page 19

research
04/16/2020

SQE: a Self Quality Evaluation Metric for Parameters Optimization in Multi-Object Tracking

We present a novel self quality evaluation metric SQE for parameters opt...
research
03/05/2019

Virtual Ground Truth, and Pre-selection of 3D Interest Points for Improved Repeatability Evaluation of 2D Detectors

In Computer Vision, finding simple features is performed using classifie...
research
11/03/2020

Shift If You Can: Counting and Visualising Correction Operations for Beat Tracking Evaluation

In this late-breaking abstract we propose a modified approach for beat t...
research
05/04/2021

Towards Error Measures which Influence a Learners Inductive Bias to the Ground Truth

Artificial intelligence is applied in a range of sectors, and is relied ...
research
10/25/2012

Performance Evaluation of Random Set Based Pedestrian Tracking Algorithms

The paper evaluates the error performance of three random finite set bas...
research
07/18/2017

A Machine Learning Approach for Evaluating Creative Artifacts

Much work has been done in understanding human creativity and defining m...
research
04/26/2019

Synthetic Ground Truth Generation for Evaluating Generative Policy Models

Generative Policy-based Models aim to enable a coalition of systems, be ...

Please sign up or login with your details

Forgot password? Click here to reset