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Salient object detection aims to detect the attractive objects on images and videos. In this paper, we propose a novel salient object detection method for videos based on cross-frame cellular automata. Given a video, we first represent the video frames with super-pixels, and construct a saliency propagation network among super-pixels within a frame and between adjacent frames based on their appearance...
In this paper, with the help of controllable active near-infrared (NIR) lights, we construct near-infrared differential (NIRD) images. Based on reflection model, NIRD image is believed to contain the lighting difference between images with and without active NIR lights. Two main characteristics based on NIRD images are exploited to conduct spoofing detection. Firstly, there exist obviously spoofing...
Region-based Image Retrieval (RBIR), which bases itself on image segmentation rather than global features or key-point-based local features, is a branch of Content-based Image Retrieval. This paper proposes a novel RBIR-oriented image segmentation algorithm named Edge Integrated Minimum Spanning Tree (EI-MST). The difference between EI-MST and the traditional MST-based methods is that EI-MST generates...
Exercise is considered as an effective mean against overweight and obesity-related diseases. In this paper, a real-time activity recognition and counting approach is proposed to evaluate amount of exercise only using a wearable smart watch. First, accelerometer and gyroscope data are collected to extract efficient features. Then Support Vector Machine classifiers are trained to recognize nine common...
Research of named entity recognition (NER) on electrical medical records (EMRs) focuses on verifying whether methods to NER in traditional texts are effective for that in EMRs, and there is no model proposed for enhancing performance of NER via deep learning from the perspective of multiclass classification. In this paper, we annotate a real EMR corpus to accomplish the model training and evaluation...
Most existing vision-based methods for gaze tracking need a tedious calibration process. In this process, subjects are required to fixate on a specific point or several specific points in space. However, it is hard to cooperate, especially for children and human infants. In this paper, a new calibration-free gaze tracking system and method is presented for automatic measurement of visual acuity in...
It is a challenging problem to realize a robust and low cost gaze estimation system. Most existing feature-based gaze estimation methods strongly rely on cornea reflections, which are unstable to glasses, head movements and natural light. In this paper, we propose a novel gaze estimation method without use of cornea reflections based on a stereo camera system. Firstly, 3D Active Shape Models (ASM)...
Pedestrian counting is widely used in civilian surveillance. In this paper, we present a people counting system which estimates the number of people across multiple cameras with partial overlapping Fields Of Views (FOVs). The main contributions of this paper include: 1) we propose a multi-object detection and tracking method by means of synthesizing the local-feature-level information into object-level...
People counting has attracted much attention in video surveillance. This paper proposes an online adaptive learning people counting system across multiple cameras with partial overlapping Fields Of Views (FOVs). The main novelty of this system is that: 1) we propose an online adaptive learning scheme to detect and count people in order to make the system adaptive to various scenes. The system can...
People counting is a challenging task and has attracted much attention in the area of video surveillance. In this paper, we present an efficient self-learning people counting system which can count the exact number of people in a region of interest. This system based on bag-of-features model can effectively detect the pedestrians some of which are usually treated as background because they are static...
Palmprint recognition has attracted much attention in recent years. Many algorithms based texture coding achieve high accuracy. However they are still sensitive to local unsteady region introduced by variations of hand pose and other conditions. In this paper we proposed a novel feature extraction algorithm, namely binary contrast context vector (BCCV), to represent multiple contrast distribution...
As an important application in civilian surveillance, pedestrian counting is challenging due to the occlusion and cluttered background. In this paper, we present an efficient people counting system based on regression and template matching. This method can effectively overcome the shortcomings of pedestrian detecting and tracking-based method and feature regression-based method. At the same time,...
In order to make clothing, furniture, cars and other products design more in line with ergonomic principles, analysis of convex and concave surface features of the human body and its measurement methods is necessary. Body surface is constituted by a number of curved surfaces and convex and concave characteristic of these surfaces can be quantified with angle value. Convex and concave characteristic...
Crowd density analysis is crucial for crowd monitoring and management. This paper proposes a novel method for crowd density analysis. According to the framework, input images are firstly divided into patches, and each patch is associated with a density label based on its texture features. Finally, local information is synthesized for global density estimation. Local image content is described by features...
In this paper, we propose a new algorithm for shape initialization and 3D pose alignment in Active Shape Model (ASM). Instead of initializing with average shape in previous works, we build a scatter data interpolation model from key points to obtain the initial shape, which ensures shape initialized around face organs. These key points are chosen from organs of face shape and located with a strong...
Many previous image processing methods discard low-frequency components of images to extract illumination invariant for face recognition. However, this method may cause distortion of processed images and perform poorly under normal lighting. In this paper, a new method is proposed to deal with illumination problem in face recognition. Firstly, we define a score to denote a relative difference of the...
A novel pedestrian detection method that integrates context information with slide window search is proposed. The method applies notions such as corner, motion, and appearance to localize pedestrians in far-field videos without performing brute-force-search. The corners direct attention to a set of conspicuous locations as the starting points for searching. And motion detection restricts the searching...
Image registration is the process of overlaying two or more images of the same scene taken at different times, from different view points, and /or by different sensors. A novel feature-based multi-sensor image registration system is developed. The system consists of two new points: first, edge features are extracted from images, and the features are dilated to suppress some certain kinds of noise...
This paper researches on the issue of computer recognition to the handwritten character images, including lowercase letters and Arabic numerals. In this paper, we preprocess on characters in order to unified the basic features. And then, we apply the basic method of making the grids to extract the features of character, and classify the respectives. At last, we apply the latest heuristic modifications...
In this paper, a new feature for text verification is proposed. The difficulties for the selection of features for text verification (FTV) are first discussed, followed by two principles for the FTV: the FTV should minimize the influence of backgrounds, and it should also be expressive enough for all the texts varied in structures prominently. In this paper, we exploit different block partition methods...
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