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81.
82.
Social signal processing: Survey of an emerging domain 总被引:3,自引:1,他引:2
The ability to understand and manage social signals of a person we are communicating with is the core of social intelligence. Social intelligence is a facet of human intelligence that has been argued to be indispensable and perhaps the most important for success in life. This paper argues that next-generation computing needs to include the essence of social intelligence – the ability to recognize human social signals and social behaviours like turn taking, politeness, and disagreement – in order to become more effective and more efficient. Although each one of us understands the importance of social signals in everyday life situations, and in spite of recent advances in machine analysis of relevant behavioural cues like blinks, smiles, crossed arms, laughter, and similar, design and development of automated systems for social signal processing (SSP) are rather difficult. This paper surveys the past efforts in solving these problems by a computer, it summarizes the relevant findings in social psychology, and it proposes a set of recommendations for enabling the development of the next generation of socially aware computing. 相似文献
83.
J.G. Taylor M. Hartley N. Taylor C. Panchev S. Kasderidis 《Image and vision computing》2009,27(11):1641
We present a neural network software architecture, guided by that of the human and more generally primate brain, for the construction of an autonomous cognitive system (which we have named GNOSYS). GNOSYS is created so as to be able to attend to stimuli, to conceptualise them, to learn their predicted reward value and reason about them so as to attain those stimuli in the environment with greatest predicted value. We apply this software system to an embodied version in a robot, and describe the activities in the various component modules of GNOSYS, as well as the overall results. We briefly compare our system with some others proposed to have cognitive powers, and finish by discussion of future developments we propose for our system, as well as expanding on the arguments for and against our approach to creating such a software system. 相似文献
84.
Yu Ma 《Information Sciences》2009,179(6):830-843
Color deficient persons, especially dichromats, have difficulty in discriminating certain kinds of colors. To help dichromats discriminate colors better, a color transformation method is proposed. The method utilizes the redundancy of color information, changing the colors of a scene into discernable ones for dichromats. The self-organizing map (SOM) algorithm is used to build a nonlinear color map, maintaining the neighboring relations between colors. Results of both subjective observation and quantitative evaluation show that the method can effectively enhance the color discrimination for dichromats. This study provides a new approach to rectify color vision deficiency. 相似文献
85.
Since color recording and color representing abilities of various media are very different, color information is often lost or misrepresented in the process of image transmission and reproduction. A Color Management System (CMS) based on iCAM color appearance model is presented in this paper. It can be used either in computer operation system software or application software for obtaining color consistency across different software applications, imaging devices, imaging media and viewing conditions. 相似文献
86.
Benchmarking Image Segmentation Algorithms 总被引:1,自引:0,他引:1
We present a thorough quantitative evaluation of four image segmentation algorithms on images from the Berkeley Segmentation
Database. The algorithms are evaluated using an efficient algorithm for computing precision and recall with regard to human
ground-truth boundaries. We test each segmentation method over a representative set of input parameters, and present tuning
curves that fully characterize algorithm performance over the complete image database. We complement the evaluation on the
BSD with segmentation results on synthetic images. The results reported here provide a useful benchmark for current and future
research efforts in image segmentation. 相似文献
87.
We present a simple and robust feature preserving image regularization by letting local region measures modulate the diffusivity.
The purpose of this modulation is to disambiguate low level cues in early vision. We interpret the Ambrosio-Tortorelli approximation
of the Mumford-Shah model as a system with modulatory feedback and utilize this interpretation to integrate high level information
into the regularization process. The method does not require any prior model or learning; the high level information is extracted
from local regions and fed back to the regularization step. An important characteristic of the method is that both negative
and positive feedback can be simultaneously used without creating oscillations. Experiments performed with both gray and color
natural images demonstrate the potential of the method under difficult noise types, non-uniform contrast, existence of multi-scale
patterns and textures.
相似文献
Sibel Tari (Corresponding author)Email: |
88.
在分析BOSA器件结构的基础上,提出一种基于图像分析的TO焦距测试与自动激光焊接方案. TO由气缸驱动从初始点向上单步移动,通过图像系统采集光斑图像,并基于OpenCV分析,通过比较分析结果,得到期望的TO位置.移动T0使焦点落在插芯与圆方管体的贴合面,并在此处进行激光焊接.实验表明,该系统具有良好的准确性和实用性. 相似文献
89.
Kailas Vodrahalli Achintya K. Bhowmik 《Journal of the Society for Information Display》2017,25(11):676-694
Recent advances in the field of computer vision can be attributed to the emergence of deep learning techniques, in particular convolutional neural networks. Neural networks, partially inspired by the brain's visual cortex, enable a computer to “learn” the most important features of the images it is shown in relation to a specific, specified task. Given sufficient data and time, (deep) convolutional neural networks offer more easily designed, more generalizable, and significantly more accurate end‐to‐end systems than is possible with previously employed computer vision techniques. This review paper seeks to provide an overview of deep learning in the field of computer vision with an emphasis on recent progress in tasks involving 3D visual data. Through a backdrop of the mammalian visual processing system, we hope to also provide inspiration for future advances in automated visual processing. 相似文献
90.
Keerthy Kusumam Tomáš Krajník Simon Pearson Tom Duckett Grzegorz Cielniak 《野外机器人技术杂志》2017,34(8):1505-1518
This paper describes a 3D vision system for robotic harvesting of broccoli using low‐cost RGB‐D sensors, which was developed and evaluated using sensory data collected under real‐world field conditions in both the UK and Spain. The presented method addresses the tasks of detecting mature broccoli heads in the field and providing their 3D locations relative to the vehicle. The paper evaluates different 3D features, machine learning, and temporal filtering methods for detection of broccoli heads. Our experiments show that a combination of Viewpoint Feature Histograms, Support Vector Machine classifier, and a temporal filter to track the detected heads results in a system that detects broccoli heads with high precision. We also show that the temporal filtering can be used to generate a 3D map of the broccoli head positions in the field. Additionally, we present methods for automatically estimating the size of the broccoli heads, to determine when a head is ready for harvest. All of the methods were evaluated using ground‐truth data from both the UK and Spain, which we also make available to the research community for subsequent algorithm development and result comparison. Cross‐validation of the system trained on the UK dataset on the Spanish dataset, and vice versa, indicated good generalization capabilities of the system, confirming the strong potential of low‐cost 3D imaging for commercial broccoli harvesting. 相似文献