In this work, multi-frame thermal imagery of the face a person is employed for drunk identification. Regions with almost constant temperature on sober and persons are thoroughly examined their capability to discriminate intoxication. Novel image processing approaches as well feature extraction techniques developed support identification procedure. These constitute novel ideas in theory analysis...

This paper presents a multi-person vision tracking approach based on human body localization features to address the problem of interactive object and in home monitoring scenario. Firstly, model is used obtain 3D position body, which then construct motion Kalman filter method. At same time, appearance constructed by fusing color histogram oriented gradient better characterize body. Secondly, ob...

Much research has been devoted in recent years to recognizing human action from video images. Most existing methods, however, take video of people from the outside making it difficult to understand behavioral intention. The First Person Vision approach has been proposed in response to this problem. In this approach, a device consisting of two cameras collectively called an “inside-out camera” i...

Egocentric videos are characterised by their ability to have the first person view. With the popularity of Google Glass and GoPro, use of egocentric videos is on the rise. Recognizing action of the wearer from egocentric videos is an important problem. Unstructured movement of the camera due to natural head motion of the wearer causes sharp changes in the visual field of the egocentric camera c...

This paper presents a novel appearance-based method for person re-identification. The core idea is to rank and select different body parts on the basis of the discriminating power of their characteristic features. In our approach, we first segment the pedestrian images into meaningful parts, then we extract features from such parts as well as from the whole body and finally, we perform a salien...

In this paper, we address the problem of person detection in indoor videosurveillance data. We present a new method based on the state of the art integral channel features. This approach is extended to allow the use of temporal features in addition to appearance based features. The temporal features are integrated by a robust background subtraction method. Our method is then evaluated on severa...

Person recognition aims at recognizing the same identity across time and space with complicated scenes and similar appearance. In this paper, we propose a novel method to address this task by training a network to obtain robust and representative features. A key observation is that traditional cross entropy loss only enforces the inter-class variation among samples and ignores to narrow down th...

A robust and reliable person detection is crucial for many applications. In the domain of service robots that we focus on, knowing the location of a person is an essential requirement for any meaningful human-robot interaction. In this work we present a people detection algorithm exploiting RGB-D data from Kinect-like cameras. Two features are obtained from the data representing the geometrical...