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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...
In this paper, we propose a dynamic gesture spotting and recognition algorithm using our stereovision system. The 3D trajectories of hand gestures are first reconstructed by a stereovision-based motion capture platform. Hand gestures can then be segmented from the trajectory in real time by using proposed gesture spotting algorithm. Discrete cosine transforms coefficients, complex index and gesture...
This paper presents a new approach for efficient object detection and matching in images and videos. We propose a stage based on a classification scheme that classifies the extracted features in new images into object features and non-object features. This binary classification scheme has turned out to be an efficient tool that can be used for object detection and matching. By means of this classification...
In this paper, a system which constructs a mosaic image of the tunnel surface with little distortion is presented. The tunnel surface is typically composed of a roughly cylindrical surface and protuberant regions containing objects such as pipes, pans and tunnel ridges. Since the true surface is neither planar nor quadric, existing mosaicing methods, which assume either homography or quadratic motion...
In this paper we present a new method for categorizing video sequences capturing different scene classes. This can be seen as a generalization of previous work on scene classification from single images. A scene is represented by a collection of 3D points with an appearance based codeword attached to each point. The cloud of points is recovered by using a robust SFM algorithm applied on the video...
We present a semi-automatic system that converts conventional video shots to stereoscopic video pairs. The system requires just a few user-scribbles in a sparse set of frames. The system combines a diffusion scheme, which takes into account the local saliency and the local motion at each video location, coupled with a classification scheme that assigns depth to image patches. The system tolerates...
The goal of this research is to recognize an object and its orientation in space by using stereo camera. The principle of object orientation recognition in this paper was based on the scale invariant feature transform (SIFT) and support vector machine (SVM). SIFT has been successfully implemented on object recognition but it had a problem recognizing the object orientation. For many autonomous robotics...
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