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Related Experiment Video

Updated: Jul 7, 2026

Long-term Behavioral Tracking of Freely Swimming Weakly Electric Fish

Long-term Behavioral Tracking of Freely Swimming Weakly Electric Fish

Published on: March 6, 2014

Tracking visible boundary of objects using occlusion adaptive motion snake.

Y Fu, A T Erdem, A M Tekalp

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society

|February 12, 2008

Summary

This study introduces a new method for tracking video object boundaries during occlusion. The technique accurately detects and tracks visible contours using segmented prediction and scale-invariant energy terms for robust occlusion handling.

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Last Updated: Jul 7, 2026

Long-term Behavioral Tracking of Freely Swimming Weakly Electric Fish

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Long-term Video Tracking of Cohoused Aquatic Animals: A Case Study of the Daily Locomotor Activity of the Norway Lobster (Nephrops norvegicus)

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Published on: April 8, 2019

Area of Science:

Computer Vision
Image Processing
Video Analysis

Background:

Object boundary tracking in videos is challenging due to occlusions.
Existing methods often struggle with accurate occlusion detection and boundary prediction.

Purpose of the Study:

To develop a novel technique for tracking the visible boundary of a video object, even when occluded.
To enable accurate occlusion detection and visible boundary determination.

Main Methods:

Utilizes piecewise contour prediction based on local motion and color information.
Employs contour snapping with scale-invariant intra-frame and inter-frame energy terms.
Models motion on both sides of contour segments for occlusion analysis.

Main Results:

The proposed technique accurately determines whether and where a tracked boundary is occluded.
Scale/resolution-independent snake energy terms facilitate multi-resolution tracking without parameter retuning.
Demonstrates high accuracy in contour prediction at coarse resolution and snapping at fine resolution.

Conclusions:

The novel technique effectively tracks visible object boundaries in videos despite occlusions.
The developed snake energy terms and piecewise prediction enhance occlusion detection and boundary tracking accuracy.
The method supports multi-resolution tracking, improving overall performance and applicability.