Proceedings of the 8th international conference on Intelligent user interfaces
Robust tracking of human body parts for collaborative human computer interaction
Computer Vision and Image Understanding
Recognizing Plant Species by Leaf Shapes-A Case Study of the Acer Family
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 2 - Volume 2
Detecting Pedestrians Using Patterns of Motion and Appearance
International Journal of Computer Vision
Approximate Bayesian Multibody Tracking
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Framework for Model-Based Tracking Experiments in Image Sequences
International Journal of Computer Vision
International Journal of Computer Vision
Robust real-time vision for a personal service robot
Computer Vision and Image Understanding
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This paper proposes a recognition and count method of leaves on the surface of a river to be used in mangrove ecosystem monitoring. Conventionally counting leaves required considerable manual labor for precise monitoring of material flow in the ecosystem. Therefore an efficient counting method was needed. Our method automatically recognizes and counts the number of floating leaves in recorded video using color and motion features. The color feature is represented by 3 dimensional histogram of a color space. We have developed a user interface based on the interactive machine learning model to acquire the color feature from video images. The user can easily produce a huge number of sample data to extract the color feature by the user interface in the same way as coloring a picture. For the motion feature, speed and acceleration of the targets are used. The counting method proposed in this paper has been applied to three videos (total five hours) which recorded about 20,000 leaves, and high recall and precision rates of 96% and 94%, respectively, have been achieved.