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Zhaoxiang Liu

Publications and source records attributed to Zhaoxiang Liu.

81 records · Page 5Linked to original sources

A Realistic Face-to-Face Conversation System based on Deep Neural Networks

To improve the experiences of face-to-face conversation with avatar, this paper presents a novel conversation system. It is composed of two sequence-to-sequence models respectively for listening and speaking and a Generative Adversarial Network (GAN) based realistic avatar synthesizer. The models exploit the facial action and head pose to learn natural human reactions. Based on the models' output, the synthesizer uses the Pixel2Pixel model to generate realistic facial images. To show the improvement of our system, we use a 3D model based avatar driving scheme as a reference. We train and evaluate our neural networks with the data from ESPN shows. Experimental results show that our conversation system can generate natural facial reactions and realistic facial images.

cs.CV↗

Deep Global-Relative Networks for End-to-End 6-DoF Visual Localization and Odometry

Although a wide variety of deep neural networks for robust Visual Odometry (VO) can be found in the literature, they are still unable to solve the drift problem in long-term robot navigation. Thus, this paper aims to propose novel deep end-to-end networks for long-term 6-DoF VO task. It mainly fuses relative and global networks based on Recurrent Convolutional Neural Networks (RCNNs) to improve the monocular localization accuracy. Indeed, the relative sub-networks are implemented to smooth the VO trajectory, while global subnetworks are designed to avoid drift problem. All the parameters are jointly optimized using Cross Transformation Constraints (CTC), which represents temporal geometric consistency of the consecutive frames, and Mean Square Error (MSE) between the predicted pose and ground truth. The experimental results on both indoor and outdoor datasets show that our method outperforms other state-of-the-art learning-based VO methods in terms of pose accuracy.

cs.CV↗

Wearable Travel Aid for Environment Perception and Navigation of Visually Impaired People

This paper presents a wearable assistive device with the shape of a pair of eyeglasses that allows visually impaired people to navigate safely and quickly in unfamiliar environment, as well as perceive the complicated environment to automatically make decisions on the direction to move. The device uses a consumer Red, Green, Blue and Depth (RGB-D) camera and an Inertial Measurement Unit (IMU) to detect obstacles. As the device leverages the ground height continuity among adjacent image frames, it is able to segment the ground from obstacles accurately and rapidly. Based on the detected ground, the optimal walkable direction is computed and the user is then informed via converted beep sound. Moreover, by utilizing deep learning techniques, the device can semantically categorize the detected obstacles to improve the users' perception of surroundings. It combines a Convolutional Neural Network (CNN) deployed on a smartphone with a depth-image-based object detection to decide what the object type is and where the object is located, and then notifies the user of such information via speech. We evaluated the device's performance with different experiments in which 20 visually impaired people were asked to wear the device and move in an office, and found that they were able to avoid obstacle collisions and find the way in complicated scenarios.

cs.CV↗

Virtual-Blind-Road Following Based Wearable Navigation Device for Blind People

To help the blind people walk to the destination efficiently and safely in indoor environment, a novel wearable navigation device is presented in this paper. The locating, way-finding, route following and obstacle avoiding modules are the essential components in a navigation system, while it remains a challenging task to consider obstacle avoiding during route following, as the indoor environment is complex, changeable and possibly with dynamic objects. To address this issue, we propose a novel scheme which utilizes a dynamic sub-goal selecting strategy to guide the users to the destination and help them bypass obstacles at the same time. This scheme serves as the key component of a complete navigation system deployed on a pair of wearable optical see-through glasses for the ease of use of blind people's daily walks. The proposed navigation device has been tested on a collection of individuals and proved to be effective on indoor navigation tasks. The sensors embedded are of low cost, small volume and easy integration, making it possible for the glasses to be widely used as a wearable consumer device.

cs.CV↗

Deep Learning Based Robot for Automatically Picking up Garbage on the Grass

This paper presents a novel garbage pickup robot which operates on the grass. The robot is able to detect the garbage accurately and autonomously by using a deep neural network for garbage recognition. In addition, with the ground segmentation using a deep neural network, a novel navigation strategy is proposed to guide the robot to move around. With the garbage recognition and automatic navigation functions, the robot can clean garbage on the ground in places like parks or schools efficiently and autonomously. Experimental results show that the garbage recognition accuracy can reach as high as 95%, and even without path planning, the navigation strategy can reach almost the same cleaning efficiency with traditional methods. Thus, the proposed robot can serve as a good assistance to relieve dustman's physical labor on garbage cleaning tasks.

cs.CV↗

Electronic quantum coherence induced by strong field molecular ionization

The existence of electronic coherence can fundamentally change the scenario of nonlinear interaction of light with quantum systems such as atoms and molecules, which, however, has escaped from observation in the investigations of strong field nonlinear optics in the past several decades. Here, we report on the generation of electronic quantum coherence by strong field ionization of nitrogen molecules in an intense 800 nm laser field. The coherence is experimentally revealed by observing a resonant four-wave mixing process in which the two pump pulses centered at 800 nm and 1580 nm wavelengths are temporally separated from each other. The experimental observation is further reproduced by calculating the nonlinear polarization response of N_2^+ ions using a three-level quantum model. Our result suggests that strong field ionization provides a unique approach to generating a fully coherent molecular wavepacket encapsulating the rotational, vibrational, and electronic states.

physics.optics↗

Near-resonant Raman amplification in the rotational quantum wavepackets of nitrogen molecular ions generated by strong field ionization

Generation of laser-like narrow bandwidth emissions from nitrogen molecular ions generated in intense near- and mid-infrared femtosecond laser fields has aroused much interest because of the mysterious physics underlying such a phenomenon as well as the potential application of such an effect in atmospheric spectroscopic sensing. Here, we perform a pump-probe measurement on the nonlinear interaction of rotational quantum wavepackets of nitrogen molecular ions generated in mid-infrared (e.g., at a wavelength centered at 1580 nm) femtosecond laser fields with an ultrashort probe pulse whose broad spectrum overlaps both P- and R-branch rotational transition lines between the upper and lower electronic states. The results show that in the near-resonant conditions, stimulated Raman amplification can efficiently occur which converts the broad bandwidth ultrashort probe pulse into the narrow bandwidth laser-like beam. Our finding provides an insight into the physical mechanism of strong field induced lasing actions in atmospheric environment.

physics.optics↗

Smart Guiding Glasses for Visually Impaired People in Indoor Environment

To overcome the travelling difficulty for the visually impaired group, this paper presents a novel ETA (Electronic Travel Aids)-smart guiding device in the shape of a pair of eyeglasses for giving these people guidance efficiently and safely. Different from existing works, a novel multi sensor fusion based obstacle avoiding algorithm is proposed, which utilizes both the depth sensor and ultrasonic sensor to solve the problems of detecting small obstacles, and transparent obstacles, e.g. the French door. For totally blind people, three kinds of auditory cues were developed to inform the direction where they can go ahead. Whereas for weak sighted people, visual enhancement which leverages the AR (Augment Reality) technique and integrates the traversable direction is adopted. The prototype consisting of a pair of display glasses and several low cost sensors is developed, and its efficiency and accuracy were tested by a number of users. The experimental results show that the smart guiding glasses can effectively improve the user's travelling experience in complicated indoor environment. Thus it serves as a consumer device for helping the visually impaired people to travel safely.

cs.HC↗

Generation of bright laser-like coherent emissions from nitrogen molecular ions in intense infrared laser fields: A unique quantum system for extreme nonlinear optics

We report on an investigation of simultaneous generation of several narrow-bandwidth laser-like coherent emissions from nitrogen molecular ions ( ) produced in intense mid-infrared laser fields. With systematic examinations on the dependences of coherent emissions on gas pressure as well as several laser parameters including laser intensity, polarization and wavelength of the pump laser pulses, we reveal that the multiple coherent emission lines generated in originate from a series of nonlinear processes beginning with four-wave mixing, followed with stimulated Raman scattering. Our analyses further show that the observed nonlinear processes are greatly enhanced at the resonant wavelengths, giving rise to high conversion efficiencies from the infrared pump laser pulses to the coherent emission lines near the transition wavelengths between the different vibrational energy levels of ground X and that of the excited B states.

physics.optics↗