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Real-time Face Detection and Tracking of Animals

Burghardt, T and Calic, J (2006) Real-time Face Detection and Tracking of Animals In: 8th Seminar on Neural Network Applications in Electrical Engineering, 2006-09-26 - 2006-09-27, Belgrade, Serbia.

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This paper presents a real-time method for extracting information about the locomotive activity of animals in wildlife videos by detecting and tracking the animals' faces. As an example application, the system is trained on lions. The underlying detection strategy is based on the concepts used in the Viola-Jones detector [1], an algorithm that was originally used for human face detection utilising Haar-like features and AdaBoost classifiers. Smooth and accurate tracking is achieved by integrating the detection algorithm with a low-level feature tracker. A specific coherence model that dynamically estimates the likelihood of the actual presence of an animal based on temporal confidence accumulation is employed to ensure a reliable and temporally continuous detection/tracking capability. The information generated by the tracker can be used to automatically classify and annotate basic locomotive behaviours in wildlife video repositories. © 2006 IEEE

Item Type: Conference or Workshop Item (Conference Paper)
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Vision Speech and Signal Processing
Authors :
Burghardt, T
Calic, J
Date : 1 January 2006
DOI : 10.1109/NEUREL.2006.341167
Contributors :
Related URLs :
Additional Information : © 2006 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Depositing User : Symplectic Elements
Date Deposited : 02 Dec 2014 12:53
Last Modified : 31 Oct 2017 17:10

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