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We address how human pose in 3D can be tracked from a monocular video using a probabilistic inference method. Human body is modeled as a number of cylinders in space, each with an appearance facet as well as a pose facet. The appearance facets are acquired in a learning phase from some beginning frames of the input video. On this the visual hull description of the target human subject constructed...
This paper presents a new approach for efficient object detection and matching in images and videos. We propose a stage based on a classification scheme that classifies the extracted features in new images into object features and non-object features. This binary classification scheme has turned out to be an efficient tool that can be used for object detection and matching. By means of this classification...
Battery-powered wireless embedded smart cameras have limited processing power, memory and energy. Since video processing tasks consume significant amount of power,the problem of limited resources becomes even more pronounced, and necessitates designing light-weight algorithms suitable for embedded platforms. In this paper, we present a resource-efficient salient foreground detection and tracking algorithm...
We propose a new method for view-invariant action recognition based on the rank constraint on the family of planar homographies associated with triplets of body points. We represent action as a sequence of poses and we use the fact that the family of homographies associated with two identical poses would have rank 4 to gauge similarity of the pose between two subjects, observed by different perspective...
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...
This paper proposes a method for estimating extrinsic camera parameters using video images and position data acquired by GPS. In conventional methods, the accuracy of the estimated camera position largely depends on the accuracy of GPS positioning data because they assume that GPS position error is very small or normally distributed. However, the actual error of GPS positioning easily grows to the...
We describe a method for generating an informative wide-view image using images captured by a moving camera. The generated image allows for events in the scene observed by the camera to be understood easily. Our method does not use 3D shape information explicitly. Instead, it employs the trajectory of feature points across multiple images and generates a composite image by taking into account 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...
This paper presents a novel method to count people for video surveillance applications. The problem is faced by establishing a mapping between some scene features and the number of people. Moreover, the proposed technique takes specifically into account problems due to perspective. In the experimental evaluation, the method has been compared with respect to the algorithm by Albiol et al., which provided...
The knowledge about the body orientation of humans can improve speed and performance of many service components of a smart-room. Since many of such components run in parallel, an estimator to acquire this knowledge needs a very low computational complexity. In this paper we address these two points with a fast and efficient algorithm using the smart-room's multiple camera output. The estimation is...
In this paper, we propose a novel dual pass video stabilization system using iterative motion estimation and adaptive motion smoothing. In the first pass, the transformation matrix to stabilize each frame is returned. The global motion estimation is carried out by a novel iterative method. The intentional motion is estimated using adaptive window smoothing. Before the beginning of the second pass,...
Based on the camera calibration principle of Tsai's two stage method, a vehicle speed measurement method by video was put forward and the error analysis of camera calibration and vehicle speed measurement were carried out in this paper. Firstly, the internal and external parameters of the camera were gained based on Tsai's two stage method. Secondly, the displacement offset of the same vehicle's feature...
The use of camera as a biometric sensor is desirable due to its ubiquity and low cost, especially for mobile devices. Palm print is an effective modality in such cases due to its discrimination power, ease of presentation and the scale and size of texture for capture by commodity cameras. However, the unconstrained nature of pose and lighting introduces several challenges in the recognition process...
This paper presents a novel disparity map refinement method and vision based surveillance framework for the task of detecting objects of interest in dynamic outdoor environments from two stereo video sequences taken at different times and from different viewing angles by a mobile camera platform. The proposed framework includes several steps, the first of which computes disparity maps of the same...
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...
In this paper, we propose a novel approach for video stabilization using Markov random field (MRF) modeling and maximum a posteriori (MAP) optimization. We build an MRF model describing a sequence of unstable images and find joint pixel matchings over all image sequences with MAP optimization via Gibbs sampling. The resulting displacements of matched pixels in consecutive frames indicate the camera...
In this paper we propose a new technique for refinement of depth maps. The technique exploits a stereoscopic pair of images and full-pixel precision disparity map in order to produce the output disparity map with sub-pixel precision. The technique employs view synthesis for verification of hypotheses on disparity values, which are formed to iteratively improve the disparity map. Results of experiments,...
This paper introduces an intelligent high-frame-rate video logging system that can automatically detect high-speed unpredictable behavior and record video comprising images with dimensions of 512 × 512 pixels at 1000 fps. To capture high-frame-rate video of crucial moments of abnormal behavior in high-speed periodic motion, a real-time abnormal behavior detection algorithm is implemented on a highspeed...
Detecting moving objects is a significant component in many machine vision systems. One of the challenges in real world motion detection is the unstability of the background. An ideal method is expected to reliably detect interesting movements from videos while ignoring background/uninteresting movements. In this paper, Genetic Programming (GP) based motion detection method is used to tackle this...
VRAPS (Visual Rhythm-based Audio Playback System) is an interactive multimedia application that uses a novel visual rhythm detection technique to allow a user to control the playback speed of an audio signal by moving in front of a video camera. As traditionally defined in the context of music, a beat represents a distinctive musical event such as the hitting of a drum or the start of a new melodic...
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