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Due to an increasing demand for video surveillance, there is an explosive growth of surveillance videos, which causes a big challenge in video storage, browsing, and retrieval. The video synopsis technique is thus developed to extract and rearrange the moving objects so as to handle the massive video browsing challenge. However, the traditional video synopsis (TVS) method only considers the processing...
Recently, pedestrian attributes like gender, age and clothing etc., have been used as soft biometric traits for recognizing people. Unlike existing methods that assume the independence of attributes during their prediction, we propose a multi-label convolutional neural network (MLCNN) to predict multiple attributes together in a unified framework. Firstly, a pedestrian image is roughly divided into...
Due to illumination changes, partial occlusions, and object scale differences, person re-identification over disjoint camera views becomes a challenging problem. To address this problem, a variety of image representations have been put forward. In this paper, the illumination invariance and distinctiveness of different color models including the proposed color model are firstly evaluated. Since color...
Various hand-crafted features and metric learning methods prevail in the field of person re-identification. Compared to these methods, this paper proposes a more general way that can learn a similarity metric from image pixels directly. By using a "siamese" deep neural network, the proposed method can jointly learn the color feature, texture feature and metric in a unified framework. The...
In recent years, large-scale video search and mining has been an active research area. Exploring the trajectory of pedestrian of interest in non-overlapping multi-camera network, namely the trajectory mining, is very useful for visual surveillance and criminal investigation. The trajectory mentioned in our work describes the transition of pedestrian among cameras from a macroscopic perspective which...
Face recognition, which is security-critical, has been widely deployed in our daily life. However, traditional face recognition technologies in practice can be spoofed easily, for example, by using a simple printed photo. In this paper, we propose a novel face liveness detection approach to counter spoofing attacks by recovering sparse 3D facial structure. Given a face video or several images captured...
Face antispoofing has now attracted intensive attention, aiming to assure the reliability of face biometrics. We notice that currently most of face antispoofing databases focus on data with little variations, which may limit the generalization performance of trained models since potential attacks in real world are probably more complex. In this paper we release a face antispoofing database which covers...
This study focuses on the design of an intelligent machine vision and sorting system. The vision system uses an artificial neural network trained to perform recognition. A Bluetooth communication link facilitates communication between the intelligent recognition system and a robot control computer. Image feature vectors are transmitted to the remote control computer for recognition and a robot control...
We report the extension of Frequency-Domain Holography to a Frequency-Domain Streak Camera capable of capturing the evolution of refractive index structures propagating at luminal speeds. Possibility of extension to Frequency-Domain Tomography is demonstrated.
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