비디오 추적
아래의 예제에서는 카메라에서 녹화된 비디오를 사용하여 영역 내의 표적을 추적합니다.
추천 예제
Import Camera-Based Datasets in MOT Challenge Format for Object Tracking
Read camera image sequences and import ground truth and detections in MOT Challenge format.
- R2023a 이후
- 라이브 스크립트 열기
Implement Simple Online and Realtime Tracking
Implement the Simple Online and Realtime (SORT) object tracking algorithm.
- R2023a 이후
- 라이브 스크립트 열기
Multi-Object Tracking with DeepSORT
Integrate appearance features from a re-Identification (Re-ID) Deep Neural Network with a multi-object tracker to improve the performance of camera-based object tracking. The implementation closely follows the Deep Simple Online and Realtime (DeepSORT) multi-object tracking algorithm [1]. This example uses the Sensor Fusion and Tracking Toolbox™ and the Computer Vision Toolbox™.
- R2023b 이후
- 라이브 스크립트 열기
Visual Tracking of Occluded and Unresolved Objects
Resolve challenging tracking scenarios when objects are occluded and in close proximity.
- R2023a 이후
- 라이브 스크립트 열기
Reidentify People Throughout a Video Sequence Using ReID Network
Track people throughout a video sequence using re-identification with a residual network.
- R2023b 이후
- 라이브 스크립트 열기
Automate Ground Truth Labeling for Object Tracking and Re-Identification
Create an automation algorithm to automatically label data for object tracking and for object re-identification.
- R2024a 이후
- 라이브 스크립트 열기
Convert Ground Truth Labeling Data for Object Tracking
Convert a groundTruth
object to the trackCLEARmetrics
truth format.
- R2024a 이후
- 라이브 스크립트 열기
Convert Ground Truth Labeling Data for Object Re-Identification
Convert a groundTruth
object to the re-identification training data format.
- R2024a 이후
- 라이브 스크립트 열기
Multi-Object Tracking and Human Pose Estimation
Detect multiple people, track them, and estimate their body poses in a video by using pretrained deep learning networks and a global nearest-neighbor (GNN) assignment tracking approach.
- R2024a 이후
- 라이브 스크립트 열기
MATLAB 명령
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