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Automated detection of elephants in wildlife video

EURASIP JOURNAL ON IMAGE AND VIDEO PROCESSING 2013年第1期2013卷 1页

作者： Zeppelzauer, Matthias Vienna Univ Technol Interact Media Syst Grp Inst Software Technol & Interact Syst A-1040 Vienna Austria

Biologists often have to investigate large amounts of video in behavioral studies of animals. These videos are usually not sufficiently indexed which makes the finding of objects of interest a time-consuming task. We propose a fully automated method for the detection and tracking of elephants in wildlife video which has been collected by biologists in the field. The method dynamically learns a color model of elephants from a few training images. based on the color model, we localize elephants in video sequences with different backgrounds and lighting conditions. We exploit temporal clues from the video to improve the robustness of the approach and to obtain spatial and temporal consistent detections. The proposed method detects elephants (and groups of elephants) of different sizes and poses performing different activities. The method is robust to occlusions (e. g., by vegetation) and correctly handles camera motion and different lighting conditions. Experiments show that both near-and far-distant elephants can be detected and tracked reliably. The proposed method enables biologists efficient and direct access to their video collections which facilitates further behavioral and ecological studies. The method does not make hard constraints on the species of elephants themselves and is thus easily adaptable to other animal species.

关键词： Automated video indexing color-based object detection Automatic animal detection Elephant detection object tracking

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An efficient omnidirectional vision system for soccer robots: From calibration to object detection

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MECHATRONICS 2011年第2期21卷 399-410页

作者： Neves, Antonio J. R. Pinho, Armando J. Martins, Daniel A. Cunha, Bernardo Univ Aveiro ATRI IEETA DETI P-3810193 Aveiro Portugal

Robotic soccer is nowadays a popular research domain in the area of multi-robot systems. In the context of RoboCup, the Middle Size League is one of the most challenging. This paper presents an efficient omnidirectional vision system for real-time object detection, developed for the robotic soccer team of the University of Aveiro, CAMBADA. The vision system is used to find the ball and white lines, which are used for self-localization, as well as to find the presence of obstacles. Algorithms for detecting these objects and also for calibrating most of the parameters of the vision system are presented in this paper. We also propose an efficient approach for detecting arbitrary FIFA balls, which is an important topic of research in the Middle Size League. The experimental results that we present show the effectiveness of our algorithms, both in terms of accuracy and processing time, as well as the results that the team has been achieving: 1st place in RoboCup 2008, 3rd place in 2009 and 1st place in the mandatory technical challenge in RoboCup 2009, where the robots have to play with an arbitrary standard FIFA ball. (C) 2010 Elsevier Ltd. All rights reserved.

关键词： Robotic vision Omnidirectional vision systems color-based object detection Shape-based object detection Vision system calibration

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