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The availability of 3D sensors has recently made it possible to capture depth maps in real time, which simplifies a variety of visual recognition tasks, including object/action classification, 3D reconstruction, etc.We address here the problems of human action recognition in depth sequences. On one hand, we present a new joint shape-motion descriptor which(More)
Abstract-With the explosion in demand for visual information retrieval in soccer videos, many Content-Based Video Retrieval (CBVR) models were born. However these current CBVR models still remain some shortcomings such as inflexible retrieval frameworks because they are majorly based on a specific training data set and a specific language. In this paper we(More)
Recently, the Microsoft Kinect sensor has provided the whole new type of data in computer vision, the depth information. The most important contribution of depth information is to overcome one of the hardest parts in visual information extraction, the segmentation process. Especially in human action recognition field, the depth data help reduce the noise(More)
We investigate the problem of human action recognition by studying the effects of fusing feature streams retrieved from color and depth sequences. Our main contribution is two-fold: First, we present the so-called 3DS-HONV descriptor which is a spatio-temporal extension of Histogram of Oriented Normal vector (HONV), specifically designed for capturing the(More)
Abstract-On-screen text is a rich information resource to query events in soccer video due to its close relation to what happens on the screen. However, low resolution, clutter background, unknown font, size, color, etc. prevent the efforts of using this resource for querying. This paper presents a novel approach for querying events in soccer video using(More)
Reading text in scene images is a challenging task and is still an active research nowadays. The difficulties come from low resolution, complex background, non uniform lightning or blurring effects of scene images. This paper focuses on recognizing characters in scene images based on the feature learning method proposed in [6] and the conclusion on(More)
RGB-D cameras offer both color and depth images of the surrounding environment, making them an attractive option for robot sensor. In this work, we present an RGB-D SLAM system using the Microsoft Kinect. The proposed system is a full 6DoF (Degrees of Freedom) SLAM system which can estimate camera trajectory and reconstruct a 3D model of the environment in(More)