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High Dynamic Range Imaging is a inevitable step in machine vision for a high dynamically illuminated environment. In cost-wise aspect it is better to convert the high dynamic image to a low dynamic one with preserving the maximum information with the help of Tone Reproduction Algorithm. Another essential feature in colour based object recognition is colour constancy, especially in identifying metal...
Practical tracking system must be able to adjust the tracking windows adaptively according to the size-changes of the tracked objects; otherwise it can not track the objects with obvious size-changes accurately. Based on the visual theory, and combined with the primal sketch of the objects extracted by the Otsu method as well as the changes of the elements-number as the measure information, this paper...
In recent years several works have aimed at exploiting color information in order to improve the bag-of-words based image representation. There are two stages in which color information can be applied in the bag-of-words framework. Firstly, feature detection can be improved by choosing highly informative color-based regions. Secondly, feature description, typically focusing on shape, can be improved...
Color and texture are visual cues of different nature, their integration in a useful visual descriptor is not an obvious step. One way to combine both features is to compute texture descriptors independently on each color channel. A second way is integrate the features at a descriptor level, in this case arises the problem of normalizing both cues. A significant progress in the last years in object...
The Local Binary Pattern (LBP) operator is a computationally efficient yet powerful feature for analyzing local texture structures. While the LBP operator has been successfully applied to tasks as diverse as texture classification, texture segmentation, face recognition and facial expression recognition, etc., it has been rarely used in the domain of Visual Object Classes (VOC) recognition mainly...
Visual object recognition is one of the most challenging problems in computer vision, due to both inter-class and intra-class variations. The local appearance-based features, especially SIFT, have gained a big success in such a task because of their great discriminative power. In this paper, we propose to adopt two different kinds of feature to characterize different aspects of object. One is the...
Generally the bag-of-words based image representation follows a bottom-up paradigm. The subsequent stages of the process: feature detection, feature description, vocabulary construction and image representation are performed independent of the intentioned object classes to be detected. In such a framework, combining multiple cues such as shape and color often provides below-expected results. This...
This paper presents a new descriptor for object categorization and pedestrian identification applications. One of the main drawbacks of shape-context descriptor is its vulnerability and distinctness to color images. We propose a spherical descriptor that simultaneously adopts the spatial and color information as a discriminative representation. Based on the descriptor, this paper also contributes...
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