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This paper aims to develop an effective flower classification approach using the technology of feature extraction. With this regard, a fused descriptor based on Pyramid Histogram of Visual Words (PHOW) is used to extract the color, texture and contour information of flower image. Secondly, Dictionary Learning and Locality-constrained Linear Coding (LLC) are operated on PHOW feature and then images...
Semi-automatic 2D-to-3D conversion becomes very popular in 3D contents creation due to its advantages over balancing the tradeoff between labor cost and 3D conversion effect. However, the key-frame extraction, as a very important step, has not been specifically put forward in the existing systems. In this paper, a novel key-frame extraction method based on cumulative occlusion is proposed for 2D-to-3D...
A visual codebook serves as a fundamental component in many state-of-the-art computer vision systems. Most existing codebooks are built based on quantizing local feature descriptors extracted from training images. Subsequently, each image is represented as a high-dimensional bag-of-words histogram. Such highly redundant image description lacks efficiency in both storage and retrieval, in which only...
This paper proposed a parallel particle filter algorithm with the help of GPU (Graphic Processing Unit) in face tracking. Due to illumination and occlusion problems, face tracking usually does not work stably based on a single cue. Three different visual cues, color histogram, edge orientation histogram and wavelet feature, are integrated under the framework of particle filter to improve the tracking...
This paper proposed a multi-cue based face tracking algorithm with the help of parallel multi-core processing. Due to illumination and occlusion problems, face tracking usually does not work stably based on a single cue. Three different visual cues, color histogram, edge orientation histogram and wavelet feature, are integrated under the framework of particle filter to improve the tracking performance...
Salient region of the image, which is composed of salient or interest points, is the most informative part of the image. In this paper, a saliency-based bottom-up visual attention computational model motivated by visual physiological experimental results is used to detect salient region and extract salient points of images. Meanwhile, a method to select number of the salient points to be extracted...
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