Xiangang Cheng

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This paper presents an efficient and effective solution for retrieving image near-duplicate (IND) from image database. We introduce the coherent phrase model which incorporates the coherency of local regions to reduce the quantization error of the bag-of-words (BoW) model. In this model, local regions are characterized by visual phrase of multiple(More)
Large-scale dataset construction will require a significant large amount of well labeled ground truth. For the NUS-WIDE dataset, a less labor-intensive annotation process was used and this paper will focuses on improving the semi-manual annotation method used. For the NUS-WIDE dataset, improving the average accuracy for top retrievals of individual concepts(More)
Age-related macular degeneration (AMD) is a leading cause of vision loss. The presence of drusen are often associated to AMD. Drusen are tiny yellowish-white extracellular buildup present around the macular region of the retina. Clinically, ophthalmologists examine the area around the macula to determine the presence and severity of drusen. However, manual(More)
The fovea (centre of the retinal macula region) is responsible for central vision. Conditions which can affect the macula region in particular include AMD and macular oedema, which lead to a direct loss in visual acuity due to the effect on central vision. The detection of the fovea is an important step in the assessment of retinal images for pathologies(More)
The macula is the part of the eye responsible for central high acuity vision. Detection of the macula is an important task in retinal image processing as a landmark for subsequent disease assessment, such as for age-related macula degeneration. In this paper, we have presented an approach to automatically determine the macula centre in retinal fundus(More)
Retinal landmark detection is a key step in retinal screening and computer-aided diagnosis for different types of eye diseases, such as glaucomma, age-related macular degeneration(AMD) and diabetic retinopathy. In this paper, we propose a semantic image transformation(SIT) approach for retinal representation and automatic landmark detection. The proposed(More)
The current volume of videos available for distribution or viewing on the internet is increasing exponentially, there is an urgent need for designing effective and efficient video management systems. However, due to the tremendous amounts of video data, it is highly likely that any large scale video systems will provide query results with near-duplicates(More)
This paper presents an efficient and effective solution for retrieving Image Near-Duplicate (IND). Different from traditional methods, we analyze the local dependencies among region descriptors in a spatial-scale space. Such local dependencies in spatial-scale space(LDSS) encodes not only visual appearance but also the spatial and scale co-occurrence of(More)