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| 1 | Modeling plants with sensor data显示文摘Sensor data, typically images and laser data, are essential to modeling real plants. However, due to the complex geometry of the plants, the measurement data are generally limited, thereby bringing great difficulties in classifying and constructing plant organs, comprising leaves and branches. The paper presents an approach to modeling plants with the sensor data by detecting reliable sharp features, i.e. the leaf apexes of the plants with leaves and the branch tips of the plants without leaves, on volumes recovered from the raw data. The extracted features provide good estimations of correct positions of the organs. Thereafter, the leaves are reconstructed separately by simply fitting and optimizing a generic leaf model. One advantage of the method is that it involves limited manual intervention. For plants without leaves, we develop an efficient strategy for decomposition-based skeletonization by using the tip features to reconstruct the 3D models from noisy laser data. Experiments show that the sharp feature detection algorithm is effective, and the proposed plant modeling approach is competent in constructing realistic models with sensor data. | MA Wei XIANG Bo ZHA HongBin LIU Jia ZHANG XiaoPeng | 2009 | Science in China(Series F)2009，52，3： | 3 |
| 2 | Geometric interpretations of the relation between the image of the absolute conic and sphere images 显示文摘 | Ying Xianghua Zha Hongbin | 2006 | 1EEE Transactions on Pattern Analysis and Machine Intelligence2006，28，12： | 1 |
| 3 | Riemannian manifold learning显示文摘 | LIN Tong ZHA Hongbin | 2008 | IEEE Transactions on Pattern Analysis and Machine Intelligence2008，30，5： | 1 |
| 4 | Geometric In- terpretations of the Relation between the Image of the Absolute Conic and Sphere Images 显示文摘 | Ying XiangHua Zha Hongbin | 2006 | IEEE Trans on PAMI2006，12，28： | 1 |
| 5 | Robust human tracking based on multi-cue integration and mean-shift 显示文摘 | Liu Hong Yu Ze Zha Hongbin | 2009 | Pattern Recognition Letters2009，30，9： | 1 |
| 6 | Robust Human Tracking Based on Multi-Cue Integration and Mean-Shift显示文摘 | Liu Hong Yu Ze Zha Hongbin | | 0，，09： | 1 |
| 7 | Robust human tra- cking based on multi-cue integration and mean-shift 显示文摘 | Liu Hong Yu Ze Zha Hongbin | 2009 | Pattern RecognitionLetters2009，30，9： | 1 |
| 8 | Riemannian Manifold Learning for Nonlinear Dimensionality Reduction显示文摘 | Lin Tony Zha Hongbin Lee Sang Uk | | 0，，： | 1 |
| 9 | Multi-modal tracking of people using laser scanners and video camera 显示文摘 | Cui Jinshi Zha Hongbin Zhao Huijing | 2008 | Image and Vision Computing2008，26，2： | 1 |
| 10 | Riemannian Manifold Learning显示文摘 | Lin Tong Zha Hongbin | | 0，，05： | 1 |
| 11 | Riemannian manifold learning显示文摘 | Lin Tong Zha Hongbin | 2008 | IEEE Transactions on Pattern Analysis and Machine Intelligence2008，30，5： | 1 |
| 12 | Riemannian manifold learning显示文摘 | Lin T Zha Hongbin Lee S U | 2008 | IEEE Transactions on Pattern Analysis and Machine Intelligence2008，30，5： | 1 |
| 13 | Riemannian manifold learn ing for nonlinear dimensionality reduction显示文摘 | LIN T ZHA Hongbin LEE S U | 2006 | Lecture Notes in Computer Science2006，3951，： | 1 |
| 14 | Flow-based SLAM:From geometry computation to learning显示文摘Simultaneous localization and mapping(SLAM)has attracted considerable research interest from the robotics and computer-vision communities for>30 years.With steady and progressive efforts being made,modern SLAM systems allow robust and online applications in real-world scenes.We examined the evolution of this powerful perception tool in detail and noticed that the insights concerning incremental computation and temporal guidance are persistently retained.Herein,we denote this temporal continuity as a flow basis and present for the first time a survey that specifically focuses on the flow-based nature,ranging from geometric computation to the emerging learning techniques.We start by reviewing two essential stages for geometric computation,presenting the de facto standard pipeline and problem formulation,along with the utilization of temporal cues.The recently emerging techniques are then summarized,covering a wide range of areas,such as learning techniques,sensor fusion,and continuous time trajectory modeling.This survey aims at arousing public attention on how robust SLAM systems benefit from a continuously observing nature,as well as the topics worthy of further investigation for better utilizing the temporal cues. | Zike YAN Hongbin ZHA | 2019 | Virtual Reality & Intelligent Hardware2019，1，5： | 0 |
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