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This article is concerned with on-line counting of harmful insects of certain species in videos in the framework of in situ video-surveillance that aims at the early detection of prominent pest attacks in greenhouse crops. The video-processing challenges that need to be coped with concern mainly the low spatial resolution and color contrast of the objects of interest in the videos, the outdoor issues...
Camera handoff is an important problem when using multiple cameras to follow a number of objects in a video network. However, almost all the handoff techniques rely on a robust tracker. State-of-the-art techniques used to evaluate the performance of camera handoff use either annotated videos or simulated data, and the handoff performance is evaluated in conjunction with a tracker. This does not allow...
Captions in videos play a significant role for automatically understanding and indexing video content, since much semantic information is associated with them. This paper presents an effective approach to extracting captions from videos, in which multiple different categories of features (edge, color, stroke etc.) are utilized, and the spatio-temporal characteristics of captions are considered. First,...
This paper describes an approach to segment and locate people in crowded scenarios with application to a surveillance system for airport dependencies. To obtain robust operation, the system analyzes a variety of visual cues -color, motion and shape- and integrates them optimally. A general method for automatic inference of optimal cue integration rules is presented. This schema, based on supervised...
This paper presents a novel method for reflection removal in the context of an object detection system. The method is based on chromatic properties of the reflections and does not require a geometric model of the objects. An experimental evaluation of the proposed method has been performed on a large database, showing its effectiveness.
This paper presents an automatic face replacement approach in video based on 2D morphable model. Our approach includes three main modules: face alignment, face morph, and face fusion. Given a source image and target video, the Active Shape Models (ASM) is adopted to source image and target frames for face alignment. Then the source face shape is warped to match the target face shape by a 2D morphable...
This paper presents a new automatic approach to building a videorama with shallow depth of field. We stitch the static background of video frames and render the dynamic foreground onto the enlarged background after foreground/background segmentation. To this end, we extract the depth information from a two-view video stream. We show that the depth cues combined with color cues improve segmentation...
Sleeping posture reveals important information for eldercare and patient care, especially for bed ridden patients. Traditionally, some works address the problem from either pressure sensor or video image. This paper presents a multimodal approach to sleeping posture classification. Features from pressure sensor map and video image have been proposed in order to characterize the posture patterns. The...
Our research focuses on analysing human activities according to a known behaviorist scenario, in case of noisy and high dimensional collected data. The data come from the monitoring of patients with dementia diseases by wearable cameras. We define a structural model of video recordings based on a Hidden Markov Model. New spatio-temporal features, color features and localization features are proposed...
Methods of segmenting objects of interest from video data typically use a background model to represent an empty, static scene. However, dynamic processes in the background, such as moving foliage and water, can act to undermine the robustness of such methods and result in false positive object detections. Techniques for reducing errors have been proposed, including Markov Random Field (MRF) based...
In a consumer video, there are not only intended objects, which are intentionally captured by the camcorder user, but also unintended objects, which are accidentally framed-in. Since the intended objects are essential to present what the camcorder user wants to express in the video, discriminating the intended objects from the unintended objects are beneficial for many applications, e.g., video summarization,...
Color models are often used for representing object appearance for foreground segmentation applications. The relationships between colors can be just as useful for object selection. In this paper, we present a method of modeling color adjacency relationships. By using color adjacency models, the importance of an edge in a given application can be determined and scaled accordingly. We apply our model...
In this paper, we propose an unsupervised method for recovering the topology of multiple cameras with non-overlapping fields of view. The nodes in the topology graph are defined as entry/exit zones in each camera while the connectivity between nodes is inferred through finding continuous paths in a trellis where appearance information and temporal information of moving objects are encoded. Unlike...
This paper aims to analyze the direction of the passengers' movement according to the video shot in the public locations. The analysis result will help related departments to manage the transport situation and make a decision when confronting emergency. First, the paper realizes the detection of people's head based on Haar feature and Adaboost algorithm through OpenCV, Second, the paper investigates...
This paper presents a full motion detection system with post-processing applied to video surveillance. Motion detection is performed based on background subtraction (BGS). Our purpose is to show how an appropriate post-processing improves segmentation result provided by a BGS technique from the literature. First, BGS is performed using the codebook algorithm. Post-processing is then applied on the...
An unsupervised approach to segment the swimmer in hydrodynamic video sequences is presented in this paper. Detecting and segmenting objects in hydrodynamic scenes is challenging as both the desired foreground and unwanted background are driven by complex nonlinear dynamics. These dynamics typically comprise a chaotic mix of vortices, flows and turbulence. Medium introduced reflection and light diffraction...
In this paper, we propose the Interest Meter (IM), a system making computer conscious of user's reactions, to measure user's interest in real time. The Interest Meter takes account of users' spontaneous reactions when users interact with computers. In this work, we analyze variations of user's eye movement, blink, head motion, and facial expression. Furthermore, we propose an algorithm to combine...
This paper proposes a novel weighted feature fusion in color face recognition (FR) to automatically annotate faces in personal videos. In the proposed FR method, multiple face images (belonging to the same subject) are clustered from a sequence of video frames. To facilitate a complementary effect on improving annotation performance, the grouped faces are combined using the proposed weighted feature...
In this paper, a quasi-automatic video matting approach which can preserve the temporal consistency of the alpha mattes is presented. “Quasi-automatic” means that it only needs a few user interactions on the first frame. A new algorithm which incorporates the Bayesian Estimation, Weighted Kernel Density Estimation (WKDE) and graph cut is presented to automatically and accurately segment each frame...
The Self-Organising Artificial Neural Network Models, of which we have used the Growing Neural Gas (GNG) can be applied to preserve the topology of an input distribution. Traditionally these models neither do include local adaptation of the nodes nor colour information. In this paper, we extend GNG by presenting an improvement to the network that has both global and local properties and can track...
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