JOURNAL ARTICLE

Object tracking using deformable templates

Abstract

We propose a novel method for object tracking using prototype-based deformable template models. To track an object in an image sequence, we use a criterion which combines two terms: the deviation of the object shape from its shape in the previous frame, and the fidelity of the detected shape to the input image. Shape and gradient information are used to track the object. We have also used the consistency between corresponding object regions throughout the sequence to help in trading the object of interest. Inter-frame motion is also used to track the boundary of moving objects. We have applied the algorithm to a number of image sequences from different sources. The inherent structure in the deformable template, together with region, motion, and image gradient cues, make the algorithm relatively insensitive to the adverse effects of weak image features and moderate partial occlusion.

Keywords:
Computer vision Artificial intelligence Computer science Object (grammar) Boundary (topology) Tracking (education) Video tracking Image (mathematics) Frame (networking) Consistency (knowledge bases) Sequence (biology) Motion (physics) Pattern recognition (psychology) Mathematics

Metrics

13
Cited By
0.45
FWCI (Field Weighted Citation Impact)
26
Refs
0.61
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced Image and Video Retrieval Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Vision and Imaging
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Robotics and Sensor-Based Localization
Physical Sciences →  Engineering →  Aerospace Engineering

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