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In this paper, we present a simple yet effective visual tracking algorithm with an appearance model based on 2D discrete cosine transform (2D-DCT) representations. The DCT has the properties of decorrelation and energy compaction, and is robust against geometry and illumination changes. Hence, it is suitable for appearance modeling and the features of our appearance model are extracted from an optimized...
Fast and robust traffic sign recognition is very important but difficult for the safety driving assist systems. This study addresses the fast and robust traffic sign recognition to enhance safety driving. We first adopt the typical Hough transform methods to implement coarse-grained locating of the candidate regions (shapes of rectangle, triangle and circle, etc.) of the traffic signs; and then propose...
In traffic video surveillance system, target-level tracking and feature-level tracking are two important areas for research. Therefore, the combination between them is an interesting question. Mean-shift is a traditional target-level tracking algorithm with no adaptation to vehicle scale and orientation change. In order to solve the problem, algorithm combine SURF (speed-up robust feature) feature...
Automatic endoscope video analysis is an essential function for medical robot and computer-aided diagnosis system. However, the performance of these video analysis algorithms are often degraded by low quality endoscope images under the uncontrolled environment, where some of them are difficult even for human ourselves for analysis, such as over-saturated by reflection, too dark or obscure. In this...
A new robust lane marking detection algorithm for monocular vision is proposed. It is designed for the urban roads with disturbances and with the weak lane markings. The primary contribution of the paper is that it supplies a robust adaptive method of image segmentation, which employs jointly prior knowledge, statistical information and the special geometrical features of lane markings in the bird's-eye...
Life science researches and clinical experiment involve the positioning of the polar body. The microinjection operation of mammalian oocytes has been more and more widely used. In many cell manipulation researches, researchers need to operate the polar body of an oocyte under optical microscopy to achieve the purpose of the study. Recently, the automatic detection technology develops rapidly. The...
Cell image segmentation is one of the hot topics in medical image processing. Most of the classical cell image segmentation algorithms perform the segmentation directly on the original image and result in the loss of the cell nuclei with low intensity contrast. To solve this problem, this paper presents a novel nuclei segmentation method. Based on analyzing the characteristics of the cell nuclei,...
In this paper, we propose a novel localization method for indoor-wheeled robots. The system consists of fusing scene and range data to make more robust the 3D-to-3D egomotion estimation, which is typically done via ICP. To validate our approach and assess its performance, a system comprised of a laser range finder paired with a monocular camera is implemented and several experiments are performed...
Most robot semantic mapping methods only consider the intrinsic properties of landmarks and objects inside a scene, by detecting them with their appearances, and some other methods include extrinsic properties with manually designed object relations. In this work, we use relational operators to capture the extrinsic property values, and adopt conditional random field to integrate intrinsic and extrinsic...
This paper presents that support vector machine (SVM) is used to classify three gait patterns: level walking, stair ascent and stair descent based on ground reaction force (GRF). The recognition process consists of three stages: i) a three layers wavelet packet analysis is used for feature extraction, with which squared and standard deviation of decomposition coefficients compose features; ii) with...
With the development of artificial intelligence and pattern recognition, facial expression recognition plays a more and more important role in intelligent human-computer interaction. In this paper, we present a model named K-order emotional intensity model (K-EIM) which is based on K-Means clustering. Different from other related works, the proposed approach can quantify emotional intensity in an...
In this paper, we propose a novel pictograph detection scheme by removing miss matching points. In our previous work, we developed a robot navigation which uses only one CCD camera equipped on the robot and estimates localize self-position by pictographs on a general environment. However, our system sometimes misjudges feature points on the background as feature points on pictographs. Threfore, our...
Recently, approaches utilizing spatial-temporal features have achieved great success in human action classification. However, they typically rely on bag-of-words (BoWs) model, and ignore the spatial and temporal structure information of visual words, bringing ambiguities among similar actions. In this paper, we present a novel approach called sequential BoWs for efficient human action classification...
This paper presents a novel multi-sensor-based robot localization framework inspired by human coarse-to-fine recognition mechanism to realize fast and robust localization in the process of robot navigation. This localization framework consists of two parts: coarse place recognition and accurate location estimation. The coarse place recognition is realized using an onboard camera, whereas an image...
With the rapid development of computer vision, the Internet and robot technology, it's potential to develop a telepresence robot for providing service for people who need a real avatar. We present a real-time vision-based telepresence robot hand control system, including the hand detection, hand tracking, hand recognition, 3D hand position and hand control modules. From our experiments, the composition...
In general, it is difficult to construct an object recognition system, because such a system has many design variables and often these cannot be designed independently. However, in certain manufacturing tasks, it is not always necessary to design all variables. In this study, we selected a picking task as the target task for the experiment. We restricted the design variables to parameters of the preprocessing...
Currently in home environments, robot assisting systems with emotion understanding ability are generally achieved in two several manners. The first is the implementing of such systems in such a way that they offer general services for all considered persons without considering privacy, special needs of their interaction partners. The second way is the targetting of such systems for merely one person...
In this paper, a new method based on deep learning for robotics autonomous navigation is presented. Different from the most traditional methods based on fixed models, a convolutional neural network (CNN) modelling technique in Deep learning is selected to extract the feature inspired by the working pattern of the biological brain. This neural network model has muti-layer features where the ambient...
According to the distribution characteristics of lidar collection points, dense in the vicinity and sparse in the distance, a terrain classification method based on variable-scale three-dimensional grid map is proposed to classify an unknown terrain into four categories, which includes roads, lawns, buildings and trees. First, we establish a variable-scale three-dimensional grid map. Then the algorithm...
This paper proposes a real-time eyelid state recognition method based on a video sequence. The human eye strongly reflects the mental state of an individual, such as attention, drowsiness, stress and confusion. In recent times, the automatic identification of such mental states using non-contact eyelid state recognition technology is proving to be a promising avenue for the development of such systems...
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