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Object detection is a key issue in computer vision, and technologies based local descriptor become more and more mature, especially in pedestrian detection. In this paper, we present a novel algorithm to detect targets from an image. Local descriptor has been used in object detection for quite some time and proven to be a valuable tool. However, Local descriptors are usually accompanied by boundary...
Signature zones' identification has been used in signature recognition and verification. The identification of an offline signature requires the whole image of the signature to be processed without considering other features in the signature. One of the signature features that are frequently used as the precondition for other subsequent algorithms in signature recognition and verification is the baseline...
The Scale Invariant Feature Transform, SIFT, is invariant to image translation, scaling, rotation, and is partially invariant to illumination changes. But, the time of features extraction and matching is huge, and the number of features is much larger then that is needed. To reduce the number of features generated by SIFT as well as their extraction and matching time, a modified approach based sampling...
One of the tasks facing historians and conservationists is the authentication or dating of medieval manuscripts. To this end it is important to them to verify whether writings on the same or different manuscripts are concurrent. In this work we explore this task by capturing images of manuscript pages in infrared (IR) and modelling and then comparing the ink appearance of segmented text. The modelling...
In this paper, a semi-supervised particle filter approach is proposed for visual tracking. The combination of semi-supervised learning and particle filter is very natural since the unlabelled samples are generated by particle propagation. In addition, the proposed semi-supervised particle filter can online select different features for robust tracking. To the best knowledge of the authors, this is...
In this paper, a novel low-complexity iris recognition system based on 1-bit transform (1BT) and angular radial partitioning (ARP) is proposed. A binary iris image is obtained using 1BT on iris image. ARP is applied to this binary image and a feature vector is extracted considering the amount of data in the partitions and identification is executed. An important advantage of the proposed approach...
In this paper, we propose a semi-supervised ensemble tracking approach under the framework of particle filter. The particle filter is used not only for object searching, but also for unlabelled sample generation. By adopting the semi-supervised learning technology, these unlabelled samples which are generated online are utilized to progressively modify the classifier and make the ensemble tracker...
This work addresses the problem of classifying the genre of text, which is useful for a variety of language processing problems. We propose statistics of POS histograms as classification features, coupled with a quadratic discriminant classifier. In experiments on six different text and speech genres, we demonstrate enhanced performance compared to standard techniques using word frequency count features...
Defects in underground pipeline images are indicative of the condition of buried infrastructures like sewers and water mains. This paper entitled automated assessment Tool for the depth of pipe deterioration presents a three step method which is a simple, robust and efficient one to detect defects in the underground concrete pipes. It identifies and extracts defect-like structures from pipe images...
This paper presents novel algorithms for shot boundary detection and key frames extraction. The algorithm differs from conventional methods mainly in the use of image segmentation and attention model. Matching difference between two consecutive frames is computed with different weights. Shot boundaries are detected with automatic threshold. Key frame is extracted by using reference frame-based approach...
Image mosaicing is an effective means of constructing a single panoramic image from a series of snapshots taken in different viewing angles. However, in the case of congested traffic scenes with a cluttered environment including vehicles or pedestrians, there are severe difficulties in aligning a pair of snapshots. In such cases, some objects would be taken only in one of the image pair, thereby resulting...
In this paper, we propose a novel hierarchical framework for soccer (football) video classification. Unlike most existing video classification approaches, which focus on shot detection followed by classification based on clustering using shot aggregation, the proposed scheme perform a top-down video scene classification which avoids shot clustering. This improves the classification accuracy and also...
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