The single image containing only a human face not previously addressed in the literature is employed to estimate body height. The human face especially the facial vertical distribution possesses some important informa...
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The single image containing only a human face not previously addressed in the literature is employed to estimate body height. The human face especially the facial vertical distribution possesses some important information which strongly correlates with the stature. The vertical proportions keep up relative constancy during the human growth. Only a few facial features such as the eyes, the lip and the chin are necessary to extract. The metric stature is estimated according to the statistical measurement sets and the facial vertical golden proportion. The estimated stature is tested with some individuals with only a single facial image. The performance of the proposed method is compared with some similar methods, which shows the proposal performs better. The experimental results highlight that the developed method estimates stature with high accuracy.
An improved dual filed modular inversion algorithm which can support inversion operation in both GF(P) and GF(2∧m) is proposed in this paper. Compared with previous ones based on Extended Euclidean algorithm, it not ...
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An improved modular multiplication algorithm based on the interleaved multiplication is presented in this paper. Carry save addition (CSA), redundant representation, a fast lookup table and a counter register are used...
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This paper proposes an efficient and flexible interactive object segmentation approach using kernel density estimation based graph cuts. First, the user draws scribbles to roughly mark the interested object and backgr...
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This paper proposes an efficient and flexible interactive object segmentation approach using kernel density estimation based graph cuts. First, the user draws scribbles to roughly mark the interested object and background, respectively, and the likelihood of object versus background is evaluated for each pixel using nonparametric kernel density estimation. Then pixels are globally classified into object and background using graph cuts, which uses likelihood as data cost and gradient information to generate a spatial varying smoothness cost. If the user is not satisfied with the initially segmented object, the user is allowed to mark these undesirable regions by drawing additional scribbles. A local region for refinement is then adaptively determined, and pixel reclassification is performed to extract a more accurate object boundary. Experimental results on a variety of images demonstrate that interested objects with good visual quality can be extracted with less user interaction and a timely response.
Color differences between different views can cause performance degradation in multiview video coding. In order to overcome this problem, in this paper a local color correction method based on histogram segmentation i...
Color differences between different views can cause performance degradation in multiview video coding. In order to overcome this problem, in this paper a local color correction method based on histogram segmentation is proposed. In the proposed method, we correct the color changes in the different segmentation regions between the current picture and the reference picture. Extensive experimental results demonstrate that the proposed method outperforms the traditional global linear color correction methods with objective mean of disparity values and subjective visual quality, and achieves better correction results.
Jetting is regarded as the next generation dispensing technology due to its features of non-contact and high precision dispensing. In this paper, we developed a jetting system for chip-on-glass package consisting of a...
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This paper proposes an efficient approach to extract salient objects in an image. A scale-invariant saliency map is first constructed based on a multi-resolution feature contrast calculation, meanwhile the image is se...
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This paper proposes an efficient approach to extract salient objects in an image. A scale-invariant saliency map is first constructed based on a multi-resolution feature contrast calculation, meanwhile the image is segmented into homogenous regions using nonparametric kernel density estimation (NKDE). Then the region saliency ratio of each region combination to its complement is calculated in turn. Finally, salient objects are extracted by maximizing the region saliency ratio. Experimental results demonstrate the effectiveness of the proposed approach.
In the draft of multi-view coding (MVC), variable size motion estimation and disparity estimation are employed to select the best coding mode for each macroblock. These techniques achieve the highest possible coding e...
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In the draft of multi-view coding (MVC), variable size motion estimation and disparity estimation are employed to select the best coding mode for each macroblock. These techniques achieve the highest possible coding efficiency, but they result in extremely large computation complexity which obstructs MVC from practical application. This paper proposes a fast mode size decision algorithm for MVC in inter-frame coding. It makes use of the mode distribution correlation between neighbor views to deduct the executions of unnecessary modes. Experimental results show that the proposed fast mode decision algorithm reduces the computational complexity significantly with negligible coding efficiency.
A novel method is proposed to analyze pointing recognition based on a single un-calibrated camera. Face skin information is explicitly adopted as view quality in selecting the best view from multiple cameras. View mea...
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ISBN:
(纸本)9781849191388
A novel method is proposed to analyze pointing recognition based on a single un-calibrated camera. Face skin information is explicitly adopted as view quality in selecting the best view from multiple cameras. View measurement has been developed to overcome the effects from camera view directions and the distances between the user and the camera. No explicit constraints are set on the camera placement. Pointing users can move freely inside a wider interaction environment while pointing at some targets. The mentioned model does not constrain whether the pointing surface is flat or not. Experiments have highlighted that the proposed method is efficient and the performance of pointing recognition from the optimal viewpoint camera outperforms other cameras.
A compressed sensing (CS) based channel estima-tion algorithm is proposed by using the delay-Doppler sparsity of the fast fading channel. A compressive basis expansion chan-nel model with sparsity in both time and fre...
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A compressed sensing (CS) based channel estima-tion algorithm is proposed by using the delay-Doppler sparsity of the fast fading channel. A compressive basis expansion chan-nel model with sparsity in both time and frequency domains is given. The pilots in accordance with a novel random pilot ma-trix in both time and frequency domains are sent to measure the delay-Doppler sparsity channel. The relatively nonzero channel coefficients are tracked by random pilots at a sampling rate signifi-cantly below the Nyquist rate. The sparsity channels are estimated from a very limited number of channel measurements by the basis pursuit algorithm. The proposed algorithm can effectively improve the channel estimation performance when the number of pilot sym-bols is reduced with improvement of throughput efficiency.
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