Online searches in big image databases require sufficient results in feasible time. Digitization campaigns have simplified the access to a huge number of images in the field of art history, which can be analyzed by de...
详细信息
Online searches in big image databases require sufficient results in feasible time. Digitization campaigns have simplified the access to a huge number of images in the field of art history, which can be analyzed by detecting duplicates and similar objects in the dataset. A high recall is essential for the evaluation and therefore the search method has to be robust against minor changes due to smearing or aging effects of the documents. At the same time the computational time has to be short to allow a practical use of the online search. By using an Exemplar SVM based classifier [12] a high recall can be achieved, but the mining of negatives and the multiple rounds of retraining for every search makes the method too time-consuming. An even bigger problem is that by allowing arbitrary query regions, it is not possible to provide a training set, which would be necessary to create a classifier. To solve this, we created a pool of general negatives offline in advance, which can be used by any arbitrary input in the online search step and requires only one short training round without the time-consuming mining. In a second step, this classifier is improved by using positive detections in an additional training round. This results in a classifier for the online search in unlabeled datasets, which provides high recall in short calculation time respectively.
It is well known that the robustness of many computervision algorithms can be improved by employing large field of view cameras, such as omnidirectional cameras. To avoid obstructions in the field of view, such camer...
详细信息
ISBN:
(纸本)9781479936397
It is well known that the robustness of many computervision algorithms can be improved by employing large field of view cameras, such as omnidirectional cameras. To avoid obstructions in the field of view, such cameras need to be mounted in an exposed position. Alternatively, a multi-camera setup can be used. However, this requires the extrinsic calibration to be known. In the present work, we propose a method to calibrate a fisheye multi-camera rig, mounted on a mobile platform. The method only relies on feature correspondences from pairwise overlapping fields of view of adjacent cameras. In contrast to existing approaches, motion estimation or specific motion patterns are not required. To compensate for the large extent of multi-camera setups and corresponding viewpoint variations, as well as geometrical distortions caused by fisheye lenses, captured images are mapped into virtual camera views such that corresponding image regions coincide. To this end, the scene geometry is approximated by the ground plane in close proximity and by infinitely far away objects elsewhere. As a result, low complexity feature detectors and matchers can be employed. The approach is evaluated using a setup of four rigidly coupled and synchronized wide angle fisheye cameras that were attached to four sides of a mobile platform. The cameras have pairwise overlapping fields of view and baselines between 2.25 and 3 meters.
Moving object segmentation is an important step toward development of any computervision systems. In the present work, we have proposed a new method for segmentation of moving objects, which is based on single change...
详细信息
The objective of image fusion is to combine relevant information from two or more images of the same scene into a single composite image which is more informative and is more suitable for human and machine perception....
详细信息
Technology has made the visually impaired life more comfortable. Access to textual information has become simple to the visually impaired community. Braille is widely used as communication tool for visually impaired p...
详细信息
Moving object segmentation is an important step toward development of any computervision systems. In the present work, we have proposed a new method for segmentation of moving objects, which is based on single change...
详细信息
ISBN:
(纸本)9781467357593
Moving object segmentation is an important step toward development of any computervision systems. In the present work, we have proposed a new method for segmentation of moving objects, which is based on single change detection method applied on Contourlet coefficients of two consecutive frames. We have chosen contourlet transform as it has high directionality and represents salient features of image such as edges, curves and contours in better way as compared with wavelet transform. The proposed method is simple and does not require any other parameter except contourlet coefficients. Results after applying the proposed method for segmentation of moving objects are compared with other state-of-the-art methods in terms of visual as well as quantitative performance measures viz. Average difference, Normalized absolute error and Pixel classification based measure. The proposed method is found to be better than other methods.
The objective of image fusion is to combine relevant information from two or more images of the same scene into a single composite image which is more informative and is more suitable for human and machine perception....
详细信息
ISBN:
(纸本)9781467357593
The objective of image fusion is to combine relevant information from two or more images of the same scene into a single composite image which is more informative and is more suitable for human and machine perception. In recent past, different methods of image fusion have been proposed in literature both in spatial domain and wavelet domain. Spatial domain based methods produce spatial distortions in the fused image. Spatial domain distortion can be well handled by the use of wavelet transform based image fusion methods. In this paper, we propose a pixel-level image fusion scheme using multiresolution Biorthogonal wavelet transform (BWT). Wavelet coefficients at different decomposion levels are fused using absolute maximum fusion rule. Two important properties wavelet symmetry and linear phase of BWT have been exploited for image fusion because they are capable to preserve edge information and hence reducing the distortions in the fused image. The performance of the proposed method have been extensively tested on several pairs of multifocus and multimodal images both free from any noise and in presence of additive white Gaussian noise and compared visually and quantitatively against existing spatial domain methods. Experimental results show that the proposed method improves fusion quality by reducing loss of significant information available in individual images. Fusion factor, entropy and standard deviation are used as quantitative quality measures of the fused image.
Malaysian car plates in general appear in different character styles, types (either single or double row), sizes, spacing and character counts. Such variations cause even detecting and localizing these plates a diffic...
详细信息
ISBN:
(纸本)9781479923427
Malaysian car plates in general appear in different character styles, types (either single or double row), sizes, spacing and character counts. Such variations cause even detecting and localizing these plates a difficult problem. The problem of localization is aggravated further during night time due to poor illumination. In this paper, we introduce the idea of edgegeometrical features in detecting these plates. The edge part is obtained from the use of Difference of Gaussian operation followed by Sobel vertical edge mask. Prior to that, gamma correction is applied to increase the detection of edges. We then apply morphological operations to get the plate region candidates. Using these regions, together with the edge image, we calculate geometrical features of these regions and use rule-based classifier to correctly identify the true plate region. Finally, we test out method using our own data set which contained 250 images captured during day time and 100 images captured during night time. The result of the proposed method shows 96.9% success rate.
Traditionally stereo visual odometry algorithms estimate the robot's motion by maximizing the conditional probability of the 3D correspondences between two sets of 3D feature point positions, which were previously...
详细信息
ISBN:
(纸本)9781467356466
Traditionally stereo visual odometry algorithms estimate the robot's motion by maximizing the conditional probability of the 3D correspondences between two sets of 3D feature point positions, which were previously obtained from two consecutive stereo image pairs captured by a stereo video camera. As an alternative, in this paper a monocular visual odometry algorithm is proposed, which estimates the robot's motion by maximizing the conditional probability of the frame to frame intensity differences at observation points between two consecutive images captured by a monocular video camera. Experimental results with synthetic and real image sequences revealed highly accurate and reliable estimates, respectively. Additionally, it seems to be an excellent candidate for mobile robot missions where space, weight and power supply are really very limited.
Domes are architectural structural elements typical for ecclesiastical and secular grand buildings, like churches, mosques, palaces, capitols and city halls. The current paper targets the problem of segmentation of do...
详细信息
暂无评论