The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Based on the principle of parallax of binocular visual system, three-dimensional of target is acquired by a lot of images. One identification technique for three-dimensional (3D) target is proposed in this paper. The characteristic information of target is extracted and reconstructed after images which are collected in OpenCV are pre-processed; Finally, based on Support Vector Machine package, the...
In this paper we present a scene exploration method for the identification of interest regions in unknown indoor environments and the position estimation of the objects located in those regions. Our method consists of two stages: First, we generate a saliency map of the scene based on the spectral residual of three color channels and interest points are detected in this map. Second, we propose and...
In this article, a novel method to accurately estimate 3D surface of objects of interest is proposed. Each ray projected from 2D image plane to 3D space is modelled with the Gaussian kernel function. Then a mean shift algorithm with an annealing scheme is used to find maximums of the probability density function and recovers the 3D surface. Experimental results show that our method is more accurate...
Locating object boundaries, modeling shapes is still an interesting and important task in many applications such as computer vision, object detection, image segmentation and tracking. In this paper we show the implementation of 2D and 3D algorithms based on the level sets using the advantages residing in today's common GPUs. One main goal of this paper is to contribute a development and give one new...
This work focuses on the recognition of three-dimensional colon polyps captured by an active stereo vision sensor. The detection algorithm consists of SVM classifier trained on robust feature descriptors. The study is related to Cyclope, this prototype sensor allows real time 3D object reconstruction and continues to be optimized technically to improve its classification task by differentiation between...
Detecting pedestrians is a challenging task, which requires precise localization of pedestrians that appear in images and videos. Window-scanning based detection methods have demonstrated their promise by scanning the image densely with multi-scale detection window. However, an essential and critical issue, i.e., how to fuse these dense detections obtained through pedestrian detector and yield the...
Neuron axon analysis through confocal microscopic image stack is dedicated in visualizing the geometrical features and topological characteristics of the 3D tubular biological objects, to ascertain the morphological properties and reconstruct the connectivity of neurons. This paper proposes a new curvilinear tracking algorithm which initializes a superellipsoid kernel into the tube by fitting the...
The paper studies new constraints that characterize a 3D-motion field as observed from the relative motion of a camera. Such constraints are derived from the relative change in size of observed local image regions over time. To consider the image distortions that arise in a projective camera, a modified affine shape adaptation scheme is proposed for the case of blob detection, with an emphasis on...
Spatio-temporal salient features are widely being used for compact representation of objects and motions in video, especially for event and action recognition. The existing feature extraction methods have two main problems: First, they work in batch mode and mostly use Gaussian (linear) scale-space filtering for multi-scale feature extraction. This linear filtering causes the blurring of the edges...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.