Jiyong Ma

UNLABELLED: Biological sequence diagrams are fundamental for visualizing various functional elements in protein or nucleotide sequences that enable a summarization and presentation of existing information as well as means of intuitive new discoveries. Here, we present a software package called illustrator of biological sequences (IBS) that can be used for representing the organization of either protein or nucleotide sequences in a convenient, efficient and precise manner. Multiple options are provided in IBS, and biological sequences can be manipulated, recolored or rescaled in a user-defined mode. Also, the final representational artwork can be directly exported into a publication-quality figure. AVAILABILITY AND IMPLEMENTATION: The standalone package of IBS was implemented in JAVA, while the online service was implemented in HTML5 and JavaScript. Both the standalone package and online service are freely available at http://ibs.biocuckoo.org. CONTACT: renjian.sysu@gmail.com or xueyu@hust.edu.cn SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

This paper presents a vision of the near future in which computer interaction is characterized by natural face-to-face conversations with lifelike characters that speak, emote, and gesture. These animated agents will converse with people much like people converse effectively with assistants in a variety of focused applications. Despite the research advances required to realize this vision, and the lack of strong experimental evidence that animated agents improve human-computer interaction, we argue that initial prototypes of perceptive animated interfaces can be developed today, and that the resulting systems will provide more effective and engaging communication experiences than existing systems. In support of this hypothesis, we first describe initial experiments using an animated character to teach speech and language skills to children with hearing problems, and classroom subjects and social skills to children with autistic spectrum disorder. We then show how existing dialogue system architectures can be transformed into perceptive animated interfaces by integrating computer vision and animation capabilities. We conclude by describing the Colorado Literacy Tutor, a computer-based literacy program that provides an ideal testbed for research and development of perceptive animated interfaces, and consider next steps required to realize the vision.

In this paper, a system designed for helping the deaf to communicate with others is presented. Some useful new ideas are proposed in design and implementation. An algorithm based on geometrical analysis for the purpose of extracting invariant feature to signer position is presented. An ANN–DP combined approach is employed for segmenting subwords automatically from the data stream of sign signals. To tackle the epenthesis movement problem, a DP-based method has been used to obtain the context-dependent models. Some techniques for system implementation are also given, including fast matching, frame prediction and search algorithms. The implemented system is able to recognize continuous large vocabulary Chinese Sign Language. Experiments show that proposed techniques in this paper are efficient on either recognition speed or recognition performance.

The detection of smoke in the initial stage is vital for preventing fire events. Therefore, we present a method of smoke heatmap detection using computer vision. First, the smoke region is segmented by encoder–decoder with atrous separable convolution (Deeplabv3+), and the edge of smoke is optimized with conditional random field to achieve pixel-level detection of early fire smoke. Subsequently, the heatmap of smoke thickness based on HSV or gray feature is established, and the space–time distribution of the smoke region is analyzed. In addition, generative adversarial network is used to predict the future frames and smoke trend heatmap, which will contribute to the development of fire protection and provide suggestions for rescue or evacuation. The experimental results show that the proposed method can accurately detect the fire smoke in different scenes and provide an effective heatmap analysis scheme, as well as provides basic data for further study on the trend of fire.

We describe a system for recognizing both the isolated and continuous Chinese sign language (CSL) using two cybergloves and two 3SAPCE-position trackers as gesture input devices. To get robust gesture features, each joint-angle collected by cybergloves is normalized. The relative position and orientation of the left hand to those of the right hand are proposed as the signer position-independent features. To speed up the recognition process, fast match and frame prediction techniques are proposed. To tackle the epenthesis movement problem, context-dependent models are obtained by the dynamic programming (DP) technique. HMM are utilized to model basic word units. Then we describe training techniques of the bigram language model and the search algorithm used in our baseline system. The baseline system converts sentence level gestures into synthesis speech and gestures of a 3D virtual human synchronously. Experiments show that these techniques are efficient both in recognition speed and recognition performance.