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KI-Glossar

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Object Tracking

Algorithmic process of locating and tracking one or more moving objects in a video sequence frame by frame, using spatial and temporal information.

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Kalman Filter

Recursive state estimation algorithm that predicts the future position of an object based on its past motion and corrects these predictions with new observations.

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DeepSORT

Multi-object tracking algorithm that combines an object detector with a Kalman filter and a deep re-identification network to maintain object identities over long sequences.

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Multi-Object Tracking (MOT)

Object tracking discipline that simultaneously tracks multiple distinct entities in a video sequence while managing interactions and occlusions between them.

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Single Object Tracking (SOT)

Tracking paradigm where a single predefined object is tracked through a video sequence, typically initialized manually in the first frame.

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Siamese Networks

Twin neural network architecture that learns a similarity function to compare a template of the target object with candidate regions in subsequent frames.

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Correlation Filters

Tracking approach based on correlation in the frequency domain that maximizes the correlation response between the object model and search regions for efficient localization.

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Tracklet

Continuous temporal segment of an object's trajectory, representing a sequence of successive detections belonging to the same entity before merging with other segments.

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Re-Identification (Re-ID)

Technique for recognizing the same object after a period of absence or occlusion by comparing its unique appearance characteristics.

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Tracking-by-Detection

Tracking strategy that decouples object detection in each frame from the temporal association of detections, usually using pre-trained CNN detectors.

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Particle Filter

Sequential Monte Carlo method that represents the probability distribution of the object's state with a set of weighted particles to handle non-linear movements.

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Mean Shift

Iterative non-parametric clustering algorithm that finds the mode of a probability distribution to locate the object by following the direction of the highest feature density.

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CAMShift

Adaptive extension of Mean Shift that dynamically adjusts the size of the tracking window based on the moments of the object's color distribution.

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Online Tracking

Tracking approach that processes frames sequentially and updates trajectories in real-time without access to future frames.

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Offline Tracking

Tracking method that optimizes trajectories over the entire complete video, allowing for retroactive correction of association errors.

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Feature Matching

Process of identifying correspondences between interest points or visual descriptors from one frame to another to establish tracking continuity.

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Hungarian Algorithm

Combinatorial optimization algorithm used to solve the assignment problem between current detections and existing trajectories in multi-object tracking.

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