Recent research in mobile robot navigation make it feasible to utilize autonomous robots in service fields. But, such applications require more than just navigation. To operate in a peopled environment, robots should recognize and act according to human social behavior. In this paper, we present the design and implementation of one such social behavior: a robot that stands in line much as people do. The system employs stereo vision to recognize lines of people, and uses the concept of personal space for modeling the social behavior. Personal space is used both to detect the end of a line and to determine how much space to leave between the robot and the person in front of it. Our model of personal space is based on measurements from people forming lines. We demonstrate our ideas with a mobile robot navigation system that can purchase a cup of co#ee, even if people are waiting in line for service.

Abstract—The amount of captured video is growing with the increased numbers of video cameras, especially the increase of millions of surveillance cameras that operate 24 hours/day. Since video browsing and retrieval is time consuming, most captured video is never watched or examined. Video synopsis is an effective tool for browsing and indexing of such a video. It provides a short video representation, while preserving the essential activities of the original video. The activity in the video is condensed into a shorter period by simultaneously showing multiple activities, even when they originally occurred at different times. The synopsis video is also an index of the original video by pointing to the original time of each activity. Video synopsis can be applied to create a synopsis of endless video streams, as generated by webcams and by surveillance cameras. It can address queries like “Show in one minute the synopsis of this camera broadcast during the past day. ” This process includes two major phases: 1) an online conversion of the endless video stream into a database of objects and activities (rather than frames) and 2) a response phase, generating the video synopsis as a response to the user’s query. Index Terms—Video summary, video indexing, video surveillance. Ç 1

The world is covered with millions of webcams, many transmit everything in their field of view over the Internet 24 hours a day. A web search finds public webcams in airports, intersections, classrooms, parks, shops, ski resorts, and more. Even more private surveillance cameras cover many private and public facilities. Webcams are an endless resource, but most of the video broadcast will be of little interest due to lack of activity. We propose to generate a short video that will be a synopsis of an endless video streams, generated by webcams or surveillance cameras. We would like to address queries like “I would like to watch in one minute the highlights of this camera broadcast during the past day”. The process includes two major phases: (i) An online conversion of the video stream into a database of objects and activities (rather than frames). (ii) A response phase, generating the video synopsis as a response to the user’s query. To include maximum information in a short synopsis we simultaneously show activities that may have happened at different times. The synopsis video can also be used as an index into the original video stream. 1.

Abstract — This paper details an approach for the automatic detection and tracking of humans using multi-sensor modalities including 3D Ladar and long wave infrared (LWIR) video. By combining data from these sensors, we can detect individuals regardless of whether they are erect, crouched, prone, or partially occluded by other obstacles. Such algorithms are integral to the development and fielding of future “intelligent” unmanned ground vehicles (UGVs). In order for robots to be integrated effectively into small combat teams in the operational environment, the autonomous vehicles must maneuver safely among our troops and therefore must be capable of detecting stationary and moving people in cluttered scenes. T I.

We describe a higher-order spectral analysis-based approach for detecting people by recognizing human motion such as walking or running. The periodic attribute of human mo-tion lends itself to efficient spectral inspection. In the pro-posed method, the stride length is determined in every frame as the image sequence evolves. The bispectrum which is the Fourier transform of the triple correlation is a robust indi-cator of presence of periodicity. Triple correlation is robust as it is immune to any symmetrically distributed noise. The

Object detection is a part of our everyday lives, however, automatic object detection by computer is still an open question. In 30 years of research in computer vision, little progress has been made. This report is a survey on the most recent techniques in object detection research. First, we introduce the definition, challenges, applications and general components of the object detection system. This is followed by a review of various appearance based approaches and feature based approaches. Appearance based approaches are classified based on different classifiers into linear representation, distribution-based, support vector machines, sparse Winnow network. Meanwhile different feature based approaches are distinguished from each other by what features are being used- texture, shape, context and multiple features. Then a framework of an object detection system is