Hierarchical monitoring of people's behaviors in complex environments using multiple cameras

We present a distributed, surveillance system that works in large and complex indoor environments. To track and recognize behaviors of people, we propose the use of the Abstract Hidden Markov Model (AHMM), which can be considered as an extension of the Hidden Markov Model (HMM), where the single Markov chain in the HMM is replaced by a hierarchy of Markov policies. In this policy hierarchy, each behavior can be represented as a policy at the corresponding level of abstraction. The noisy observations are handled in the same way as an HMM and an efficient Rao-Blackwellised particle filter method is used to compute the probabilities of the current policy at different levels of the hierarchy The novelty of the paper lies in the implementation of a scalable framework in the context of both the scale of behaviors and the size of the environment, making it ideal for distributed surveillance. The results of the system demonstrate the ability to answer queries about people's behaviors at different levels of details using multiple cameras in a large and complex indoor environment.

Learning people movement model from multiple cameras for behaviour recognition

In surveillance systems for monitoring people behaviours, it is important to build systems that can adapt to the signatures of people's tasks and movements in the environment. At the same time, it is important to cope with noisy observations produced by a set of cameras with possibly different characteristics. In previous work, we have implemented a distributed surveillance system designed for complex indoor environments [1]. The system uses the Abstract Hidden Markov mEmory Model (AHMEM) for modelling and specifying complex human behaviours that can take place in the environment. Given a sequence of observations from a set of cameras, the system employs approximate probabilistic inference to compute the likelihood of different possible behaviours in real-time. This paper describes the techniques that can be used to learn the different camera noise models and the human movement models to be used in this system. The system is able to monitor and classify people behaviours as data is being gathered, and we provide classification results showing the system is able to identify behaviours of people from their movement signatures.

Coordination of multiple cameras to track multiple people

In this paper, we present a distributed surveillance system that uses multiple cheap static cameras to track multiple people in indoor environments. The system has a set of Camera Processing Modules and a Central Module to coordinate the tracking tasks among the cameras. Since each object in the scene can be tracked by a number of cameras, the problem is how to choose the most appropriate camera for each object. We propose a novel algorithm to allocate objects to cameras using the object-to-camera distance while taking into account occlusion. The algorithm attempts to assign objects in the overlapping fields of view to the nearest camera which can see the object without occlusion. Experimental results show that the system can coordinate cameras to track people properly and can deal well with occlusion.

Measuring depth accuracy in RGBD cameras

This paper presents the comparison between the Microsoft Kinect depth sensor and the Asus Xtion for computer vision applications. Depth sensors, known as RGBD cameras,
project an infrared pattern and calculate the depth from the reflected light using an infrared sensitive camera. In this research, we compare the depth sensing capabilities of the two sensors under various conditions. The purpose is to give the reader a background to whether use the Microsoft Kinect or Asus Xtion sensor to solve a specific computer vision problem. The properties of the two depth sensors were investigated by conducting a series of experiments evaluating the accuracy of the sensors under various conditions, which shows the advantages and disadvantages of both Microsoft Kinect and Asus Xtion sensor.

Identification of prey captures in Australian Fur Seals (Arctocephalus pusillus doriferus) using head-mounted accelerometers: field validation with animal-borne video cameras

This study investigated prey captures in free-ranging adult female Australian fur seals (Arctocephalus pusillus doriferus) using head-mounted 3-axis accelerometers and animal-borne video cameras. Acceleration data was used to identify individual attempted prey captures (APC), and video data were used to independently verify APC and prey types. Results demonstrated that head-mounted accelerometers could detect individual APC but were unable to distinguish among prey types (fish, cephalopod, stingray) or between successful captures and unsuccessful capture attempts. Mean detection rate (true positive rate) on individual animals in the testing subset ranged from 67-100%, and mean detection on the testing subset averaged across 4 animals ranged from 82-97%. Mean False positive (FP) rate ranged from 15-67% individually in the testing subset, and 26-59% averaged across 4 animals. Surge and sway had significantly greater detection rates, but also conversely greater FP rates compared to heave. Video data also indicated that some head movements recorded by the accelerometers were unrelated to APC and that a peak in acceleration variance did not always equate to an individual prey item. The results of the present study indicate that head-mounted accelerometers provide a complementary tool for investigating foraging behaviour in pinnipeds, but that detection and FP correction factors need to be applied for reliable field application.

Cameras and body memory create new blends of performance with visual art practice

I propose that a learnt somatic experience of dance can translate into another discipline such as visual art. In my visual art practice I combine both photography, which is traditionally seen as a still medium, and performance in order to create a new form of embodiment. I have developed two series of art works of prints and video made in response to the Australian landscape. By analyzing my method of movement and photography I will describe how an embodied dance language can result in a material outcome – a series of drawings of light and movement, a body signature made possible through old and new technology. I have activated a performative state while capturing images discovering new ways of using technology reliant upon my knowledge of dance, performance and photography. Making a human size camera to make analogue prints I gained an intuitive knowledge of light – a skill that has become foundational in performance and photography. In response to space and light in the Australian landscape I then built a custom made camera that allows for the longest possible time to capture an image. I move while taking the image and use the camera as if an eye at the end of my arm. In this way I activate dance skills and embodied knowledge of space, timing and light, opening up a radical space for new thinking, making and performing.Furthermore this process engages memory and sentiment embodied through age. Many artists have responded to the unique qualities of the Australian landscape and by using a performative/photographic approach I have engaged with my own body memory. Being brought up in the landscape and training in ballet my body has acquired memories at a cellular level. My method has given memory a voice. In doing these works I have become conscious of how unconscious memories of the space and light in the landscape is a movement vocabulary activated in a way that ‘feels’ like dancing. As an ageing person this experience is profound and the resultant materialisation of the photographs and videos leave a material record of the event. The sentiments evoked through my process bridge the past with the present, the body with the mind, memory with body and space connecting disciplines in a new way.The materialisation of artworks itself continues cross-disciplinary processes using a technique that is a continuum of the performative. Through using technology I release memory of the landscape and pixel by pixel build imagery that relies on and is a part of the performative process. It is a photographic performance dance manifesting as pigment on paper exhibited a gallery context. The exhibition allows a space for the viewer to respond - re-membering the universal the act of moving. The works titled ‘body signatures’ and ‘Fly Rhythm’ become a communicative device in the gallery context.My paper through an analysis of process and methods used in making the two series will talk to several of the subjects listed and reveal a new way of connecting performance and visual art and old and new technologies.

Desenvolvimento de um sistema moving cameras para reconstrução 3D de movimentos submersos

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Using phenological cameras to track the green up in a cerrado savanna and its on-the-ground validation

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

The Use of Digital Motion-Sensor Cameras to Capture Coyote Presence in Western Georgia

Because of their learned avoidance of humans and the dense cover provided by forested areas, observation of coyote activity is often very limited in the Southeast. In this study we used digital motion-sensor cameras to detect activity among coyote populations in various urban and rural habitats. Camera stations were placed adjacent to regenerating clear cuts, forest trails and roads, agriculture fields, residential areas, and within city parks to determine activity and presence of coyotes in these various areas. Cameras were successful in detecting coyotes in all study sites throughout the year. Coyotes appear to show no avoidance of camera stations. Cameras may be helpful in gathering general biological and activity information on coyote populations in an area.

Augmented reality in sport scenarios using cameras mounted on a tripod

[ES] In this paper we address the problem of inserting virtual content in a video sequence. The method we propose uses just image information. We perform primitive tracking, camera calibration, real and virtual camera synchronisation and finally rendering to insert the virtual content in the real video sequence. To simplify the calibration step we assume that cameras are mounted on a tripod (which is a common situation in practise). The primitive tracking procedure, which uses lines and circles as primitives, is performed by means of a CART (Classification and Regression Tree). Finally, the virtual and real camera synchronisation and rendering is performed using functions of OpenGL (Open Graphic Library). We have applied the method proposed to sport event scenarios, specifically, soccer matches. In order to illustrate its performance, it has been applied to real HD (High Definition) video sequences. The quality of the proposed method is validated by inserting virtual elements in such HD video sequence.

People counting with re-identification using depth cameras

[EN]Low cost real-time depth cameras offer new sensors for a wide field of applications apart from the gaming world. Other active research scenarios as for example surveillance, can take ad- vantage of the capabilities offered by this kind of sensors that integrate depth and visual information. In this paper, we present a system that operates in a novel application context for these devices, in troublesome scenarios where illumination conditions can suffer sudden changes. We focus on the people counting problem with re-identification and trajectory analysis.

Augmenting the effective field of view of optical tracking cameras--a way to overcome difficulties during intraoperative camera alignment

An Internet survey demonstrated the existence of problems related to intraoperative tracking camera set-up and alignment. It is hypothesized that these problems are a result of the limited field of view of today's optoelectronic camera systems, which is usually insufficiently large to keep the entire site of surgical action in view during an intervention. A method is proposed to augment a camera's field of view by actively controlling camera orientation, enabling it to track instruments as they are used intraoperatively. In an experimental study, an increase of almost 300% was found in the effective volume in which instruments could be tracked.