Stereo cameras, laser rangers and other time-of-flight ranging devices are utilized with increasing frequency as they can provide information in the 3D plane. The ability to perform real-time registration of the 3D point clouds obtained from these sensors is important in many applications. However, the tasks of locating accurate and dependable correspondences between point clouds and registrati...

With the increasing availability of low-cost – yet precise – depth cameras, “texture+depth” content has become more and more popular in several computer vision and 3D rendering tasks. Indeed, depth images bring enriched geometrical information about the scene which would be hard and often impossible to estimate from conventional texture pictures. In this paper, we investigate how the geometric ...

In this paper, we described the video high-level feature extraction systems developed at France Telecom Orange Labs (Beijing). In our systems, four categories of lowlevel visual features, namely color, edge, texture and SIFT local descriptors, were extracted. Two approaches to fusing the representative capabilities of these visual features were investigated for different runs. Under the setting...

Classification of texture images, especially those with different orientation and scale changes, is a challenging and important problem in image analysis and classification. This paper proposes an effective scheme for rotation and scale invariant texture classification using log-polar wavelet signatures. The rotation and scale invariant feature extraction for a given image involves applying a l...

As the multimedia content over the internet is increasing day by day, efficient methods for retrieval of these huge amount of data is required. Video annotation is one of the widely used methods to analyze and retrieve these huge video data. The process of video annotation is complicated as it requires a large amount of processing to analyze the contents in the video. This paper introduces a vi...

Based on the feature matching theory about SIFT (Scale-Invariant Feature Transform) keypoints, the concentric circle structure and the color feature vector of scale-invariant descriptor are proposed in this paper. In the concentric circle structure, the radiuses of the concentric circles are proportional to the scale factor, which can achieve the scale invariance. To achieve the rotation invari...

This paper describes our contribution to instance search (INS) task for TRECVID 2012. We present four approaches for this task, (i) histograms of SIFT features as feature vectors and Bhatacharya distance for similarity detection (ii) feature vector is combination of SIFT features alone, while for matching we used a basic descriptor matching algorithm (iii) IR based approach using SIFT features ...

In the context of topological mapping, the automatic segmentation of an environment into meaningful and distinct locations is still regarded as an open problem. This paper presents an algorithm to extract places online from image sequences based on the algebraic connectivity of graphs or Fiedler value, which provides an insight into how well connected several consecutive observations are. The m...

A state-of-the-art system for finding objects in images has recently been developed by David Lowe. The algorithm is termed the Scale-Invariant Feature Transform (SIFT) and intends to detect similar feature points in each of the available images and then describe these points with a feature vector which is independent of image scale and orientation. Thus feature points which correspond to differ...