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Image segmentation is a fundamental task in computer vision and a prerequisite for many applications. But what is a good segmentation? One possible answer is given by the segmentation-by-composition framework that defines a good segment as one that can easily be composed by parts of itself. However, this framework is originally based on pixels which causes several problems, among them the need for...
Conventional saliency analysis methods measure the saliency of individual pixels. The resulting saliency map inevitably loses information in the original image and finding salient objects in it is difficult. We propose to detect salient objects by directly measuring the saliency of an image window in the original image and adopt the well established sliding window based object detection paradigm.
Detecting people in occlusion and articulated pose remains a big challenging problem in computer vision. To achieve a fast and accurate human detection algorithm, Node-Combined Part Detector (NCPD) Model is proposed in this paper. We make two major contributions: (1) We propose a novel method, torso-nodes combination, to integrate part detectors. (2) We adopt stable part detectors described by Associated...
In computer vision research, object detection based on image processing is the task of identifying a designated object on a static image or a sequence of video frames. Projects based on such research works have been widely adopted to various industrial and social applications. The fields to which those applications applies includes but not limited to, security surveillance, intelligent transportation...
In this paper we introduce the design and implementation of an automatic camera servo system using improved frame differential algorithm which can be used in varying environments. The system uses frame differential algorithm which is improved by us to analyse the screen shots. In order to make sure that the moving object is always in the center of the shot, the system detects the target motion and...
Face detection is the first step for automatic face recognition system and many surveillance systems, it has been widely applied in many fields. A face detection method based on corner verifying is presented. Firstly, most of the background area is quickly filtered out by skin color detection. Then faces are detected by AdaBoost face detection algorithm combination with skin color detection, but there...
In this paper we explore the application of Genetic Programming (GP) to the problem of domain-independent image feature extraction and classification. We propose a new GP-based image classification system that extracts image features autonomously, and compare its performance against a baseline GP-based classifier system that uses human-extracted features. We found that the proposed system has a similar...
In many scenarios, domestic robot will regularly encounter unknown objects. In such cases, top-down knowledge about the object for detection, recognition, and classification cannot be used. To learn about the object, or to be able to grasp it, bottom-up object segmentation is an important competence for the robot. Also when there is top-down knowledge, prior segmentation of the object can improve...
Considering the simplicity and fast training speed of Haar-like features, the high detecting precision of HOG features, a combined method is proposed on the basis of the two features. Several rectangular features which can describe local human characteristics based on original features are added. The combined method can retain the precision of HOG features and increase the speed of detection at the...
For resolving the problem of rotation-invariant human detection in natural scene, a rotation-invariant detection algorithm based on polar-HOGs and double-scale direction estimation is proposed in this paper. The algorithm first transforms rotation of object to cycle translation by using polar coordinate mapping, then eliminates the effect of rotation by applying reverse cycle translation to p-θ mapping...
To evaluate the engineering camouflage effectiveness impersonally and exactly, based on the theory of human visual apperceive, the model is constituted on the human visual attention mechanisms. The feature maps of spatial scales are presented upon the distilled intensity, color and orientation from the input picture. The saliency map is gained from the combination of conspicuity maps. The shift of...
Selective attention in the human visual system is performed as the way that humans focus on the most important parts when observing a visual scene. Many bottom-up computational models of visual attention have been devised to get the saliency map for an image, which are data-driven or task-independent. However, studies show that the task-driven or top-down mechanism also plays an important role during...
We consider the problem of detecting targets behind walls using radar imaging technology. An image-domain based detection technique is proposed that allows to adapt to specific targets of interest. By doing so, clutter as well as targets of no-interest are strongly reduced in the radar image. The proposed detector is automatic in the sense that no or only little prior knowledge on the image statistics...
In traffic surveillance applications, automatic methods to detect abrupt changes in a traffic scene are highly desirable. A robust method is introduced for camera based assessment of scene changes based on the dynamics derived from the detected objects in the scene. The approach needs a calibrated and oriented camera but no further contextual knowledge and works even with highly fragmented trajectories...
This paper propose an object recognition method based on template match that uses both gradient and LBP feature as the template feature. We also design a binary representation and quick bitwise operation for the proposed approach.
In this paper, we proposed an approach of multi-person movement tracking in office environment without any identity conflicts. Simple image processing with frame differentiation method is applied to identify multiple human motion. An Expert System is applied to predict next camera occurrence of the tracking human. The main objective of this work is to detect and track multi-human motion using single...
Human detection is a key functionality to reach Human Robot/Computer Interaction. The human tracking is also a rapidly evolving area in computer and robot vision; it aims to explore and to follow human motion. We present in this article an intelligent system to learn human detection. The descriptors used in our system make up the combination of HOG and SIFT that capture salient features of humans...
Human movement analysis is a long-studied, but still important and challenging research area in visual surveillance. It involves many fundamental problems in computer vision such as human detection, segmentation and tracking, and higher level problems such as human gesture, action and event recognition. Shape is the most dominant cue for detecting humans due to large appearance variability. In this...
This paper presents a novel and robust approach to detect and follow a human with a mobile robotic platform. In order to follow a human, both the initial detection of human and the subsequent tracking need to be implemented. As the robot is initially static, initial human detection is done using a background subtraction technique. To remove the outliers objects, filters are formulated based on the...
We provide a practical industrial visual surveillance framework based on the notion of visual trap points. Instead of using the whole machinery of computer vision in order to verify correct workflow execution we re-factor the behavior training module to a pre-configured pool of allowed behaviors. We exploit humans' ability to distinguish tasks and allow for an automated surveillance system to accomplish...
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