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Ability to effectively and efficiently detect planes is very useful for mobile robot navigation. This is because plane structures are abundant in man-made environment. Existing methods for plane detection are derived for different kinds of input data. In this paper, we propose a plane detection method for image sequences from Kinect. The algorithm takes into account the limitation of the Kinect's...
We propose a joint learning method for object classification and localization using 3D color texture features and geometry-based segmentation from weakly-labeled 3D color datasets. Recently, new consumer cameras such as Microsoft's Kinect produce not only color images but also depth images. These reduce the difficulty of object detection dramatically for the following reasons: (a) reasonable candidates...
Recently, there are many autonomous navigation applications done in outdoor environment. However, safe navigation is still a daunting challenge in terrain containing vegetation. Thus, a study on vegetation detection for outdoor automobile navigation is investigated in this work. At the early state of our research, we focused on the segmentation of LADAR data into two classes by using local three-dimensional...
Segmentation is the process of partitioning digital images into meaningful regions. The analysis of biological high content images often requires segmentation as a first step. We propose ilastik as an easy-to-use tool which allows the user without expertise in image processing to perform segmentation and classification in a unified way. ilastik learns from labels provided by the user through a convenient...
In this paper a visual self-localization method for a humanoid robot is presented. This one is based on monocular information. The goal of this method is to obtain the position (x; y) and orientation θ of the humanoid robot inside the field of play. The methods proposed include some digital image processing algorithms and geometric interpretation to perform a 3D monocular reconstruction, that allows...
We present a new method for segmenting color images into their composite surfaces by combining color segmentation with model-based fitting utilizing sparse depth data, acquired using time-of-flight (Swissranger, PMD CamCube) and stereo techniques. The main target of our work is the segmentation of plant structures, i.e., leaves, from color-depth images, and the extraction of color and 3D shape information...
This paper presents a feature extraction method for hand gesture based on multi-layer perceptron. The feature of hand skin color in the YCbCr color space is used to detect hand gesture. The hand silhouette and features can be accurately extracted in means of binarizing the hand image and enhancing the contrast. Median and smoothing filters are integrated to remove the noise. Combinational parameters...
In this paper we present an approach to object segmentation and recognition that combines depth and color cues. We fuse information from color images with depth from a Time-of-Flight (ToF) camera to improve recognition performance under scale and viewpoint changes. Firstly, we use depth and local surface orientation extracted from the ToF image to normalize color and depth image features with regard...
This paper presents a new method for extracting planar features from noisy range data. The method encodes the local geometric information (surface normals) and global spatial information (coordinates) of 3D data points into an Enhanced Range Image (ERI) which is then clustered into a number of homogeneous groups, called Super Pixels (SPs). The Normalized Cuts (NC) method is employed to the graph built...
This paper proposes a generative method to extract 3D human pose using just a single image. Unlike many existing approaches we assume that accurate foreground background segmentation is not possible and do not use binary silhouettes. A stochastic method is used to search the pose space and the posterior distribution is maximized using Expectation Maximization (EM). It is assumed that some knowledge...
This paper provides a method for indoor semantic mapping in 3D environment. For indoor environment constructed by numerous planar surfaces, plane features are extracted and classified to build the main structure of indoor scene. To identify and cognize different objects located in indoor scene, both the position information and the color information are used in object classification. After the background...
This paper describes a device, based on stereovision, which is designed for forest inventories purposes. It captures pairs of omni-directional stereoscopic images through a fish-eye lens, from which different tri-dimensional measures can be obtained by applying a stereovision process, including image acquisition, feature and attribute extraction, feature matching and depth determination. This paper...
In this paper, we propose an efficient scheme to automatically convert existing 2D videos to 3D ones. The proposed method extracts motion information from two consecutive frames to estimate depth map for each of them. In the method, we first develop a region-based Graph cut method to fast and accurately perform motion segmentation, which is robust to large interframe motions. Then, a depth assigning...
Robust feature extraction within 3D environments is a crucial requirement for many autonomous robotic and tracking applications. 3D Laser range finders and cameras provide extremely rich data about an environment. However, the algorithms which attempt to compress the vast data sets produced by these sensors into features, tend to be fragile in the presence of sensor noise, or computationally expensive...
In this paper a content-independent, adaptive and parameter-free estimation chain for depth map generation from still-images stereo content will be described. The state-of-the-art solutions for each step of the classical chain will be analyzed as reference benchmark for our proposed implementation. Finally, comparative results will be presented and evaluated through the Middlebury Stereo Evaluation...
Depth perception, or 3D perception, can add a lot to the feeling of immersiveness in many applications such as 3D TV, 3D teleconferencing, etc. Stereopsis and motion parallax are two of the most important cues for depth perception. Most of the 3D displays today rely on stereopsis to create 3D perception. In this paper, we propose to improve user's depth perception by tracking their motions and creating...
3D object reconstruction from images involves two important parts: object identification and object modeling. Human beings are very adept at automatically identifying different objects in a scene due to the extensive training they receive over their lifetimes. Similarly, machines need to be trained to perform this task. At present, automated 3D object identification process from aerial video imagery...
We present a min-cut based method of segmenting objects in point clouds. Given an object location, our method builds a k-nearest neighbors graph, assumes a background prior, adds hard foreground (and optionally background) constraints, and finds the min-cut to compute a foreground-background segmentation. Our method can be run fully automatically, or interactively with a user interface. We test our...
We propose a simple but powerful multi-view semantic segmentation framework for images captured by a camera mounted on a car driving along streets. In our approach, a pair-wise Markov Random Field (MRF) is laid out across multiple views. Both 2D and 3D features are extracted at a super-pixel level to train classifiers for the unary data terms of MRF. For smoothness terms, our approach makes use of...
A novel system for automatic three-dimensional ink-style rendering is presented. The goal for the whole is to transmit the Chinese painting style to three-dimension models. In this system, the input artwork is first segmented into several regions used for modeling and artistic style analysis: (1) region contours and skeletons is found to build three-dimension models by surface inflation technique,...
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