Showing papers by "Gary Bradski published in 1998"

Real time face and object tracking as a component of a perceptual user interface

Abstract: As a step towards a perceptual user interface, an object tracking algorithm is developed and demonstrated tracking human faces. Computer vision algorithms that are intended to form part of a perceptual user interface must be fast and efficient. They must be able to track in real time and yet not absorb a major share of computational resources. An efficient, new algorithm is described here based on the mean shift algorithm. The mean shift algorithm robustly finds the mode (peak) of probability distributions. We first describe histogram based methods of producing object probability distributions. In our case, we want to track the mode of an object's probability distribution within a video scene. Since the probability distribution of the object can change and move dynamically in time, the mean shift algorithm is modified to deal with dynamically changing probability distributions. The modified algorithm is called the Continuously Adaptive Mean Shift (CAMSHIFT) algorithm. CAMSHIFT is then used as an interface for games and graphics.

Method and apparatus for tracking an object using a continuously adapting mean shift

Abstract: A tracking method is disclosed. The method of the present invention tracks a object using a probability distribution of the desired object. The method operates by first calculating a mean location of a probability distribution within a search window. Next, the search window is centered on the calculated mean location. The steps of calculating a mean location and centering the search window may be performed until convergence. The search window may then be resized. Successive iterations of calculating a mean, centering on the mean, and resizing the search window track an object represented by the probability distribution. In one embodiment, a flesh hue probability distribution is generated from an input video image. The flesh hue probability distribution is used to track a human head within the video image.

Computer vision control variable transformation

Abstract: The generation of control variables for computer vision is disclosed. In one embodiment of the invention, a computerized system includes a video camera and a controller. The video camera tracks an object, such as the head of a user of the computer. The controller generates control variables having sensitivity to movement of the object that varies in accordance with movement of the object from a neutral position.

Synthesizing computer input events

Abstract: Synthesizing computer input events is disclosed. In one embodiment, a computerized system includes a sensor, a controller, a utility and an application. The sensor detects external events, such as audio events and video events. The controller generates control variables in response to the external events. The utility synthesizes input events, such as joystick, mouse, and keyboard events, from the control variables. The application then utilizes these input events.

Gesture for video content navigation

Abstract: This article describes the use of gesture recognition techniques in computer vision as a natural interlace for video content navigation, and the design of a navigation andbrowsing system that caters to these natural means of computer-human interaction. For consumer applications, video content navigation presents two challenges: (1) howto parse and summarize multiple video streams in an intuitive and efficient manner, and (2) what type of interface will enhance the ease of use for video browsing andnavigation in a living room setting or an interactive environment. In this paper, we address the issues and propose the techniques that combine video content navigation with gestures, seamlessly and intuitively, in an integrated system. The current framework can incorporate speech recognition technology. We present a new type ofbrowser for browsing and navigating video content, as well as a gesture recognitioninterface for this browser. Keywords: Computer vision, pattern recognition, user interface, video content

Gesture and Speech for Video Content Navigation

Abstract: This article describes ongoing research in the use computer vision gesture and speech recognition techniques as a natural interface for video content navigation, and the design of a navigation and browsing system that caters to these natural means of computer-human interaction. For consumer applications, video content navigation presents two challenges: (1) how to parse and summarize multiple video streams in an intuitive and efficient manner, and (2) what type of interface will enhance the ease of use for video browsing and navigation in a living room setting or an interactive environment. In this paper, we address the issues and propose the techniques that combine video content navigation with gesture and speech recognition, seamlessly and intuitively, in an integrated system. We present a new type of browser for browsing and navigating video content, as well as a gesture and speech recognition interface for this browser.