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Human activity recognition has become very popular in the field of computer vision. In this paper, we present a simple, robust and computationally efficient algorithm, architecture and implementation to recognise and classify human activities in real-time using very few training data. We employ a spatio-temporal representation of human activities by combining trajectory information and invariant spatial...
We propose a modular neural network architecture in order to make easy and fast the recognition process of the ear as a biometric. Comparing with other biometrics, ear recognition has one of the best performances, even when it has not received much attention. To improve the performance for ear recognition and make a comparison with other existing methods, we used the 2D wavelet analysis with Global...
This paper deals with the issue of gradual classification of a multivariate sequence where the number of candidate time-series generators is significantly high. It proposes a prediction scheme that consists of two components: a hierarchical structure which organizes the time-series models and a decision maker tool that assigns and evolves a respective hierarchy of probabilities; the latter expresses...
We previously proposed a model for a handshake approaching motion with a voice greeting and developed a handshake robot system that applied the proposed model for embodied interaction with humans. The handshake robot system was fabricated by considering the average size of a human arm. However, small-size embodied interaction robots are required for use in homes. Therefore, in this study, a small-size...
Human face feature recognition is an important direction of the pattern recognition, and is widely used in practical applications. Because of the uncertainty of the face recognition, the impact of posture, facial expressions and the environmental, there is a lot of difficulty in recognition, and people proposed more and more identification methods in this field. This paper will introduce the development...
As robot assisted living is gaining more attentions for elderly care recently, automated human daily activity recognition becomes more important in human-robot interaction. In this paper, we proposed an approach to indoor human daily activity recognition which combines motion data and location information. One inertial sensor is worn on the right thigh of a human subject to collect motion data, while...
In this paper, a robust gait recognition algorithm based on key frame and ellipse model is proposed, which solves the problems including finding key frames on discontinuous contour segmentation and accurate feature extraction on ellipse model. Firstly, a robust extraction algorithm of key fame is introduced, which makes detection of key fames easier and more accurate. Secondly, human bodies corresponding...
The G-banding technique is routinely used for generating characteristic banding patterns for chromosome identification and karyotyping. Since G-band patterns are not static, training cytogenetics technologists to master the skills of chromosome analysis is a long process. Furthermore, the opportunities for biology students to access a wide range of different chromosome aberrations for practice are...
Real-time body pose information is very useful for many human-robot interaction applications. However, due to the motion of both human and the robot, robust body pose recognition poses a challenge in such a system design. This paper aims to locate a human body initially in the acquired image plane and then classify six body poses through image recognition. Color-space techniques and the method of...
We present a method to classify and localize human actions in video using a Hough transform voting framework. Random trees are trained to learn a mapping between densely-sampled feature patches and their corresponding votes in a spatio-temporal-action Hough space. The leaves of the trees form a discriminative multi-class codebook that share features between the action classes and vote for action centers...
Human identity recognition is an important yet under-addressed problem. Previous methods were strictly limited to high quality photographs, where the principal techniques heavily rely on body details such as face detection. In this paper, we propose an algorithm to address the novel problem of human identity recognition over a set of unordered low quality aerial images. Assuming a user was able to...
The paper deals with the issue of action recognition as an application of the new 3D time-of-flight (ToF) camera, exploiting the special ability of the device to measure distances. Segmentation of moving people is straightforward from the distance information and subsequent steps of the processing chain follow in a classical way. We describe the first results on action recognition using ToF camera...
Psychologists have proposed that many human-object interaction activities form unique classes of scenes. Recognizing these scenes is important for many social functions. To enable a computer to do this is however a challenging task. Take people-playing-musical-instrument (PPMI) as an example; to distinguish a person playing violin from a person just holding a violin requires subtle distinction of...
We consider the problem of recognizing human actions from still images. We propose a novel approach that treats the pose of the person in the image as latent variables that will help with recognition. Different from other work that learns separate systems for pose estimation and action recognition, then combines them in an ad-hoc fashion, our system is trained in an integrated fashion that jointly...
There are many computer vision algorithms developed for visual (scene and object) recognition. Some systems focus on involved learning algorithms, some leverage millions of training images, and some systems focus on modeling relevant information (features) with the goal of effective recognition. However, none of these systems come close to human capabilities. If we study human responses on similar...
This paper presents a general approach for recognition of driving maneuvers in advanced driver assistance systems (ADAS). Such systems often rely on the identification of driving maneuvers (overtaking, left turn at intersections, etc.) to improve the prediction of potential collisions or to trigger appropriate support for the driver. The proposed maneuver recognition approach combines a fuzzy rule...
The purpose of this paper is to develop a companion robot, which can display facial expressions and recognize human faces. With the 12 degrees of freedom, the robot can generate various facial expressions. In addition, a face-recognition method is proposed based on combining two complementary matching algorithms (a single-image matching algorithm and a sequential-image matching algorithm). We have...
Nowadays, malicious computer programs have attempted to attack websites, greatly affecting their availability and security. CAPTCHA (Completely Automated Public Turing test to tell Computers and Human Apart) mechanism is an effectual method in solving this problem. The prevailing implementation of CAPTCHA is 2D still image verification code, however, the developing artificial intelligence and image...
Human posture recognition is gaining increasing attention in the fields of artificial intelligence and computer vision due to its promising applications in the areas of personal health care, environmental awareness, human-computer-interaction and surveillance systems. Human posture recognition in video sequences is a challenging task which is part of the more comprehensive problem of video sequence...
In these days, human face identification is the safe technique of computer which has been developing quickly within the scope of global. In this paper, we described the basic techniques of image processing, such as different edge detection techniques, harmony variation, and the method of image and face recognition. We focused on human interface system, which was the first step to structure the target...
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