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Appearance-based action recognition can be considered as a natural extension of appearance-based object detection from the spatial to the spatio-temporal domain. Although this step seems natural, most action recognition approaches are evaluated in isolation. Towards this end the contribution of this paper is twofold. First, a view-independent approach to action recognition is proposed and second the...
Head detection may be more demanding than face recognition and pedestrian detection in the scenarios where a face turns away or body parts are occluded in the view of a sensor, but locating people is needed. In this paper, we introduce an efficient head detection approach for single depth images at low computational expense. First, a novel head descriptor is developed and used to classify pixels as...
In this paper, we address the problem of identifying multiple faces present at different distance using Light-Field Camera (LFC). Since a LFC can provide different focus (or depth) images in single capture, we are motivated to investigate its applicability to identify multiple faces at a distance by exploring its all-in-focus property. We first collect the new face dataset using LFC and then carry...
The rising need for security in the last years has led to an increased use of surveillance cameras in both public and private areas. The increasing amount of footage makes it necessary to assist human operators with automated systems to monitor and analyze the video data in reasonable time. In this paper we summarize our work of the past three years in the field of intelligent and automated surveillance...
Automatic face recognition (FR) problem has been extensively studied and applied to domains including biometrics, security, authentication, surveillance, and identification. Face recognition algorithms commonlly use high dimensional information and are therefore computationally expensive. The use of wrongly detected features can confuse the recognition process and make it even slower. This paper presents...
In order to support real-time face recognition using a wireless camera network, we design a data acquisition service to quickly and reliably acquire face images of human subjects from multiple views and to simultaneously index each acquired image into its corresponding pose. In comparison with detection of frontal faces, the detection of non-frontal faces with unknown pose is a much more challenging...
We propose here to acquire high resolution sequences of a person's face using a pan-tilt-zoom (PTZ) network camera. This capability should prove helpful in forensic analysis of video sequences as frames containing faces are tagged, and within a frame, windows containing faces can be retrieved. The system starts in pedestrian detector mode, where the lens angle is set widest, and detects people using...
Numerous digital cameras and modern phones have a face detection module, which is used to automatically focus (AF) and optimize exposure (AE). But the face detection will fail when person doesn't face the camera or the part of the face is occluded. In order to avoid such problems, we propose a fast head-shoulder detector, which uses Variable-size block Histograms of Orientated Gradients (VHOG) descriptors...
This paper presents a method of adaptation of the well-known Viola and Jones' face detector to Central Catadioptric Systems. The performance of this detector is well-known and has been well studied. Our purpose is not to evaluate the intrinsic limits of the Viola and Jones' algorithm but to evaluate the impact of central projection systems on the algorithm's behavior. 360-degree field of view sensors...
In this paper, an face-tracking camera-based assistive technology is presented for extracting head and face based gestures which are delivered to individuals who are blind. The interface is capable of tracking the head and face of an interaction partner and delivering them through the recently developed VibroGlove interface. The construction of the interface as well as its application are detailed.
A real-time eye tracking method was introduced. The method integrates several algorithms such as AdaBoost, optical flow, and Camshift. First, lighting condition was standardized, and the camera was placed below face. Second, the nostril tracking points were localized and taken as reference points. Third, the Camshift algorithm and Lucas-Kanade optical flow algorithm were respectively utilized to track...
In this paper, we study the use of facial appearance features for the re-identification of persons using distributed camera networks in a realistic surveillance scenario. In contrast to features commonly used for person reidentification, such as whole body appearance, facial features offer the advantage of remaining stable over much larger intervals of time. The challenge in using faces for such applications,...
This paper proposes a novel hardware structure and FPGA implementation method for real-time detection of multiple human faces with robustness against illumination variations and Rotated faces. These are designed to greatly improve face detection in various environments, using the Adaboost learning algorithm and MCT techniques, Rotation Transformation, which is robust against variable illumination...
In human facial behavioral analysis, Action Unit (AU) coding is a powerful instrument to cope with the diversity of facial expressions. Almost all of the work in the literature for facial action recognition is based on 2D camera images. Given the performance limitations in AU detection with 2D data, 3D facial surface information appears as a viable alternative. 3D systems capture true facial surface...
This paper describes a sensor for autonomous surveillance capable of continuously monitoring the environment, while acquiring detailed images of specific areas. This is achieved by exploiting an omnidirectional camera and a PTZ camera, assembled together on a single mount. The two cameras form a single vision sensor, since data obtained processing the two images are used in a cooperative way. This...
Vision-based people counting systems have wide potential applications including video surveillance and public resources management. Most works in the literature rely on moving object detection and tracking, assuming that all moving objects are people. In this paper, we present our people counting approach based on face detection, tracking and trajectory classification. While we have used a standard...
The last two years have witnessed the introduction and rapid expansion of products based upon large, systematically-gathered, street-level image collections, such as Google Street View, EveryScape, and Mapjack. In the process of gathering images of public spaces, these projects also capture license plates, faces, and other information considered sensitive from a privacy standpoint. In this work, we...
We present a facial feature detector for time-of-flight (TOF) cameras that extends previous work by combining a nose detector based on geometric features with a face detector. The goal is to prevent false detections outside the area of the face. To detect the nose in the image, we first compute the geometric features per pixel. We then augment these geometric features with two additional features:...
Detection of faces in cluttered scenes under arbitrary imaging conditions (pose, expression, illumination and distance) is prone to miss and false positive errors. The well-established approach of using boosted cascades of simple classifiers addresses the problem of missing faces by using fewer stages in the cascade. This constrains the misses by making detection easier, but increases the false positives...
This paper describes a system for automatically extracting meta-information on people from videos on the Web. The system contains multiple modules which automatically track people, including both faces and bodies, and clusters the people into distinct groups. We present new technology and significantly modify existing algorithms for body-detection, shot-detection and grouping, tracking, and track-clustering...
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