A Region-Based Gauss-Newton Approach to Real-Time Monocular Multiple Object Tracking

Tjaden, Henning; Schwanecke, Ulrich; Schömer, Elmar; Cremers, Daniel

doi:10.1109/tpami.2018.2884990

Cited by 71 publications

(73 citation statements)

References 41 publications

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“…The aim of region-based pose tracking is to minimize the energy function (13). Similar to previous works [22], [24], we use a Gauss-Newton method by re-writing the energy function as a non-linear re-weighted least squares problem:…”

Section: ) Region-based 6-dof Pose Estimationmentioning

confidence: 99%

Vision-Based 3D Aerial Target Detection and Tracking for Maneuver Decision in Close-Range Air Combat

Zhong¹,

Zhao²,

Ding³

et al. 2022

IEEE Access

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Automatic maneuver decision in close-range air combat depends on the situation awareness of the 3D aerial space. Optimal decision could only be made when the 3D state (e.g. 3D position, orientation and velocity) of the target aircraft is accurately provided. Together with the state of the aircraft in our side, optimal maneuver decision could be made by maximizing the situation advantage or utilizing deep reinforcement learning. On the other hand, vision-based 3D sensing methods are ideal for acquiring the 3D state of the target aircraft in close-range air combat, since radar and other sensors work badly in such short range. In this paper, we propose a novel pipeline for vision-based maneuver decision in close-range air combat. The proposed pipeline contains three main modules: 3D target detection based on Augmented Autoencoder, 3D target tracking based on segmentation and optimization, and maneuver decision based on advantage maximization and Deep Q Networks (DQN). The proposed method effectively handles the difficulties in air combat environment, such as fast movement, occlusion from cloud, etc. Experiments demonstrate that our method could robustly detect and track the target aircraft in complex environment, which provides strong priors for maneuver decision and helps to significantly improve the winning rate of short-range air combat.INDEX TERMS 3D target detection and tracking, reinforcement learning, maneuver decision, air combat.

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Section: ) Region-based 6-dof Pose Estimationmentioning

confidence: 99%

Vision-Based 3D Aerial Target Detection and Tracking for Maneuver Decision in Close-Range Air Combat

Zhong¹,

Zhao²,

Ding³

et al. 2022

IEEE Access

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“…In the initial frame, the PCF tracker uses the shared generated samples and improved expected output to train two parallel correlation filters. Then, in the present frame, according to balancing the response maps of two filters, the PCF tracker is able to detect the location of the object with the Newton method [ 14 ]. Subsequently, the PCF tracker uses Gaussian Mixture Model to add a new sample or merge the two most similar samples to generate a new sample.…”

Section: Related Workmentioning

confidence: 99%

Parallel Three-Branch Correlation Filters for Complex Marine Environmental Object Tracking Based on a Confidence Mechanism

Zhang

et al. 2020

Sensors

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Marine object tracking is critical for search and rescue activities in the complex marine environment. However, the complex marine environment poses a huge challenge to the effect of tracking, such as the variability of light, the impact of sea waves, the occlusion of other ships, etc. Under these complex marine environmental factors, how to design an efficient dynamic visual tracker to make the results accurate, real time and robust is particularly important. The parallel three-branch correlation filters for complex marine environmental object tracking based on a confidence mechanism is proposed by us. The proposed tracker first detects the appearance change and position change of the object by constructing parallel three-branch correlation filters, which enhances the robustness of the correlation filter model. Through the weighted fusion of response maps, the center position of the object is accurately located. Secondly, the Gaussian-triangle joint distribution is used to replace the original Gaussian distribution in the training phase. Finally, a verification mechanism of confidence metric is embedded in the filter update section to analyze the tracking effect of the current frame, and to update the filter sample from verification result. Thus, a more accurate correlation filter is trained to prevent model drift and achieve a good tracking effect. We found that the effect of various interferences on the filter is effectively reduced by comparing with other trackers. The experiments prove that the proposed tracker can play an outstanding role in the complex marine environment.

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“…This kind of methods can easily fall into local minima and easily fail in tracking heterogeneous objects. 18,21,22 Recently, regionbased pose tracking methods 17,23,24 have gained increasing popularity and achieved state-of-the-art performances. Region-based methods unite pose estimation and image segmentation with the 3D model simultaneously.…”

Section: Introductionmentioning

confidence: 99%

“…The object pose is estimated by iteratively optimizing the pose parameters that minimize the segmentation energy. 17 ; third column: tracking results of the proposed method. The reprojected results show that the proposed method can accurately track the object within the large range of the scale change while TPAMI19 17 failed.…”

Section: Introductionmentioning

confidence: 99%

Robust monocular 3D object pose tracking for large visual range variation in robotic manipulation via scale-adaptive region-based method

Zhou

Wang

Bao

et al. 2022

International Journal of Advanced Robotic Systems

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Many robot manipulation processes involve large visual range variation between the hand-eye camera and the object, which in turn causes object scale change of a large span in the image sequence captured by the camera. In order to accurately guide the manipulator, the relative 6 degree of freedom (6D) pose between the object and manipulator is continuously required in the process. The large-span scale change of the object in the image sequence often leads to the 6D pose tracking failure of the object for existing pose tracking methods. To tackle this problem, this article proposes a novel scale-adaptive region-based monocular pose tracking method. Firstly, the impact of the object scale on the convergence performance of the local region-based pose tracker is meticulously tested and analyzed. Then, a universal region radius calculation model based on object scale is built based on the statical analysis result. Finally, we develop a novel scale-adaptive localized region-based pose tracking model by merging the scale-adaptive radius selection mechanism into the local region-based method. The proposed method adjusts local region size according to the scale of the object projection and achieves robust pose tracking. Experiment results on synthetic and real image sequences indicate that the proposed method achieves better performance over the traditional localized region-based method in manipulator operation scenarios which involve large visual range variation.

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A Region-Based Gauss-Newton Approach to Real-Time Monocular Multiple Object Tracking

Cited by 71 publications

References 41 publications

Vision-Based 3D Aerial Target Detection and Tracking for Maneuver Decision in Close-Range Air Combat

Vision-Based 3D Aerial Target Detection and Tracking for Maneuver Decision in Close-Range Air Combat

Parallel Three-Branch Correlation Filters for Complex Marine Environmental Object Tracking Based on a Confidence Mechanism

Robust monocular 3D object pose tracking for large visual range variation in robotic manipulation via scale-adaptive region-based method

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