Tracking-learning-detection (TLD)-based video object tracking method

A target tracking and target technology, which is applied in the direction of TV, color TV, color TV parts, etc., can solve problems such as target occlusion or disappearance, tracking point change, complex background, etc., to improve processing speed, increase computing speed, and Effects of Tracking Accuracy and Robustness

Inactive Publication Date: 2013-01-16
南京征程电子科技有限公司
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AI Technical Summary

Problems solved by technology

A tracking system with excellent performance faces many challenges, such as tracking point chan

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  • Tracking-learning-detection (TLD)-based video object tracking method
  • Tracking-learning-detection (TLD)-based video object tracking method
  • Tracking-learning-detection (TLD)-based video object tracking method

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Embodiment Construction

[0036] The technical solutions and beneficial effects of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0037] The present invention improves the existing TLD algorithm in three aspects, which will be described in detail below.

[0038] 1. Design of TLD tracker based on Cell FoT+∑ method

[0039] The tracker part of the TLD is designed using the Cell FoT+∑ method, which is an efficient point tracking algorithm. Compared with the Grid FoT+FB+NCC method used in the tracker in the original TLD, not only the robustness is enhanced, but the processing speed It has also been greatly improved.

[0040]Cell FoT selects good feature points for tracking, and each feature point is assigned a local tracker, allowing the local tracker to track good drift points. After Grid FoT predicts the global movement of the target each time, the local tracker needs to be reset to the original position. If the initially selected tracking point...

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Abstract

The invention discloses a tracking-learning-detection (TLD)-based video object tracking method, which comprises the following steps of: (1) when a start frame of an object is tracked, generating an image sub-window according to given position and size information, and training a detector; (2) estimating the area of the object in a current frame according to the position and size information of the object in a previous frame by using a tracker; (3) detecting the current frame by using the detector, and finding all possible objects in the current frame; and (4) performing fusion processing on results of the tracker and the detector, judging whether the object exists in the current frame or not, returning to the step (3) to process the next frame if the object does not exist in the current frame, judging whether a tracking trajectory of the current frame is effective or not if the object exists in the current frame, giving the position of the object, returning to the step (2) to process the next frame if the tracking trajectory of the current frame is ineffective, finishing the online updating of the detector if the tracking trajectory of the current frame is effective, and returning to the step (2) to process the next frame. According to the method, the conventional TLD algorithm is improved to obtain a video object tracking algorithm which is more ideal than the TLD algorithm.

Description

technical field [0001] The invention belongs to the field of target detection and tracking, and in particular relates to an improvement for the currently emerging video tracking algorithm TLD. Background technique [0002] Target tracking is a key issue in the field of computer vision research. Its essence is to find the best position of the target in the next image frame according to the target selected in the reference image frame, and it has important research and application value in many fields. , Such as intelligent transportation systems in the civilian field, navigation, guidance, and defense systems in the military field. A tracking system with excellent performance faces many challenges, such as tracking point changes, lighting effects, fast motion, target occlusion or disappearance, complex background, etc. [0003] TLD is a long-term, online, object tracking method with minimal prior information, which mainly consists of three parts: tracker, detector and learni...

Claims

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Application Information

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IPC IPC(8): G06T7/20G06K9/62H04N5/14
Inventor 周鑫钱秋朦王从庆叶永强
Owner 南京征程电子科技有限公司
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