With the rapid development of the Internet, online reviews have touched on all aspects of our lives and have provided us with much convenience. However, they may also mislead our behavior, especially the deceptive online reviews. In order to filter out deceptive online reviews more precisely, mainly based on sentence joint topic sentiment model (SJTSM), and also integrating the good ideas of sentence latent dirichlet allocation (SenLDA) and CopulaLDA, in this paper we propose a deceptive review detection framework (DRDF) that combines the word-level, chunk-level, and sentence-level topic sentiment models to extract the reviews different features, which is regarded as the vector input of a multiple-classifier to detect deceptive reviews. It not only utilizes the correlation of different level topic-sentiment model representations of a text, but also incorporates the structure and the sentiment label information of reviews. Our compared experimental result on different public datasets has shown that its performance is superior to the existing methods of deceptive review detection.

In final approach of rendezvous between a space robot and a non-cooperative target, due to the light and the folds of heat cladding materials on the target surface, the edge of target cannot be accurately extracted by classic Canny algorithm and we are unable to complete measurement of relative position and attitude. To solve this problem, the measurement method of relative position and attitude between two non-cooperative spacecrafts based on graph cut and edge information algorithm is proposed. A circular feature of the target is chosen as the recognition and measurement object. Firstly, the edge of the circular feature on the target is accurately extracted by graph cut and edge information algorithm. Secondly, the edges are ellipse fitting. Lastly, the relative position and attitude of target is obtained by fitting ellipse parameters of binocular cameras. The simulation results show that the precision of this method is better than Canny algorithm's and it can better meet the mission requirements.

Autonomous rendezvous in close range requires adequate ground simulations due to its significant difficulties and risks. In this paper, a novel semi-physical simulation system for binocular vision guided rendezvous is established. In this system, virtual three-dimensional models of the spacecrafts and the scene are created using computer graphic technology. Accordingly, images of the binocular cameras on board chaser (servicer) spacecraft are generated and displayed on the liquid crystal displays (LCDs). As the physical component in the simulation loop, two industrial cameras photograph the virtual images on the LCDs so that real camera noise is involved. In order to perform the closed-loop simulation, image acquisition, image processing, pose measurement, chaser guidance, navigation and control, and the system's dynamic motion are conducted. Through the combination of “virtual environment” and “physical environment”, the simulation system can successfully demonstrate binocular vision guided rendezvous. Simulation data is capable to verify the key algorithms during close range rendezvous. Changing the object model and dynamic model, this system can be applied to other vision-related researches.

Space robotic system is expected to play an increasingly important role in repairing GEO (geostationary orbit) satellites in the future. To perform the servicing mission, the robotic system is firstly required to approach and dock with the target autonomously, for which the measurement of relative pose is the key. It is a challenging task since the existing GEO satellites are generally non-cooperative, i.e. no artificial mark is mounted to aid the measurement. In this paper, a method based on binocular stereo vision is proposed to estimate the pose of a GEO satellite in the final approach phase. It directly takes the natural circular feature on the GEO satellite as the recognized object. Correspondingly, an image processing and pose measurement algorithm is presented to determine the relative position and orientation of the target. This algorithm provides a closed-form solution using simple mathematics, therefore, it is suitable to space applications where the computation capability of the on-board processor is very limited. In addition, it effectively solves the orientation-duality problem for circular feature, requiring neither specific motions of the camera nor a priori knowledge about the radius of the circle. Computer simulations verify the proposed method.