Vision Based Hand Gesture Recognition Using 3D Shape Context

Hand gesture recognition is a popular topic in computer vision and makes human-computer interaction more flexible and convenient.The representation of hand gestures is critical for recognition.In this paper,we propose a new method to measure the similarity between hand gestures and exploit it for hand gesture recognition.The depth maps of hand gestures captured via the Kinect sensors are used in our method,where the 3D hand shapes can be segmented from the cluttered backgrounds.To extract the pattern of salient 3D shape features,we propose a new descriptor-3D Shape Context,for 3D hand gesture representation.The 3D Shape Context information of each 3D point is obtained in multiple scales because both local shape context and global shape distribution are necessary for recognition.The description of all the 3D points constructs the hand gesture representation,and hand gesture recognition is explored via dynamic time warping algorithm.Extensive experiments are conducted on multiple benchmark datasets.The experimental results verify that the proposed method is robust to noise,articulated variations,and rigid transformations.Our method outperforms state-of-the-art methods in the comparisons of accuracy and efficiency.

Genetic relationships among sympatric varieties of Acer mono in the Chichibu Mountains and Central Hokkaido, Japan

Acer mono Maxim. is one of the major components of cool temperate forests in Japan. Some of its many varieties are distributed sympatrically. Because of its great variability, the intraspecific taxonomy and nomenclature of the species are controversial. To understand the genetic relationships among these varieties and whether hybridization or introgression occurred among the sympatric varieties, we studied the genetic relationships among sympatric varieties of A. mono in the Chichibu Mountains (A. mono var. ambiguum, A. mono var. connivens, A. mono var. marmoratum) and Central Hokkaido (A. mono var. mayrii and A. mono var. glabrum) in Japan. Our results showed that varieties in Chichibu are genetically close, suggesting that hybridization or introgression might occur between these varieties, which could explain the higher genetic diversity of varieties in Chichibu than in Hokkaido. In contrast to the close relationships between the varieties in Chichibu, varieties in Hokkaido seemed relatively separated from each other; indeed, there may be reproductive isolation between the two varieties. The results provide new insight for the taxonomy of the varieties of A. mono, especially the sympatric varieties, in Japan.

Online belief propagation algorithm for probabilistic latent semantic analysis

Probabilistic latent semantic analysis （PLSA） is a topic model for text documents, which has been widely used in text mining, computer vision, computational biology and so on. For batch PLSA inference algorithms, the required memory size grows linearly with the data size, and handling massive data streams is very difficult. To process big data streams, we propose an online belief propagation （OBP） algorithm based on the improved factor graph representation for PLSA. The factor graph of PLSA facilitates the classic belief propagation （BP） algorithm. Furthermore, OBP splits the data stream into a set of small segments, and uses the estimated parameters of previous segments to calculate the gradient descent of the current segment. Because OBP removes each segment from memory after processing, it is memoryefficient for big data streams. We examine the performance of OBP on four document data sets, and demonstrate that OBP is competitive in both speed and accuracy for online ex- pectation maximization （OEM） in PLSA, and can also give a more accurate topic evolution. Experiments on massive data streams from Baidu further confirm the effectiveness of the OBP algorithm.

Image categorization using a semantic hierarchy model with sparse set of salient regions

Image categorization in massive image database is an important problem. This paper proposes an approach for image categorization, using sparse set of salient semantic information and hierarchy semantic label tree （HSLT） model. First, to provide more critical image semantics, the proposed sparse set of salient regions only at the focuses of visual attention instead of the entire scene was formed by our proposed saliency detection model with incorporating low and high level feature and Shotton＇s semantic texton forests （STFs） method. Second, we also propose a new HSLT model in terms of the sparse regional semantic information to automatically build a semantic image hierarchy, which explicitly encodes a general to specific image relationship. And last, we archived image dataset using image hierarchical semantic, which is help to improve the performance of image organizing and browsing. Extension experimefital results showed that the use of semantic hierarchies as a hierarchical organizing frame- work provides a better image annotation and organization, improves the accuracy and reduces human＇s effort.

Expression of PC-cell-derived growth factor in breast cancer

This study is mainly aimed at evaluating the expression of PC-cell-derived growth factor(PCDGF)in breast cancer and breast adenofibroma,and to compare with other commonly used clinical pathological indices,then to investigate the diagnostic and targeted therapeutic purpose of PCDGF in breast cancer tissue.In this study,we detected the expression of PCDGF,p53 and CerbB-2 in breast cancer tissue and the expression of PCDGF in breast adenofibroma tissue by immunohistochemical method,and analyzed the relationship between them.We found that PCDGF was expressed in most breast cancer tissue,but was not in breast adenofibroma tissue,and the expression of PCDGF was related with the tumor’s pathological category and the expression of estrogen receptor(ER)and progesterone receptor(PR)and p53,but there was no statistical dependability between PCDGF and cerbB-2.From this study,we predict that PCDGF may serve as a marker in the secondary diagnosis of breast cancer,and may participate in the generation and differentiation of breast cancer cells,and become an effective target of therapy for breast cancer.