Title

Gesture recognition

Abstract

This paper presents a method for recognizing human-hand gestures using a model-based approach. A finite state machine is used to model four qualitatively distinct phases of a generic gesture. Fingertips are tracked in multiple frames to compute motion trajectories. The trajectories are then used for finding the start and stop position of the gesture. Gestures are represented as a list of vectors and are then matched to stored gesture vector models using table lookup based on vector displacements. Results are presented showing recognition of seven gestures using images sampled at 4Hz on a SPARC-1 without any special hardware. The seven gestures are representatives for actions of Left, Right, Up, Down, Grab, Rotate, and Stop.

Notes

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Thesis Completion

1994

Semester

Spring

Advisor

Shah, Mubarak

Degree

Bachelor of Science (B.S.)

College

College of Arts and Sciences

Degree Program

Computer Science

Subjects

Arts and Sciences -- Dissertations, Academic;Dissertations, Academic -- Arts and Sciences

Format

Print

Identifier

DP0020866

Language

English

Access Status

Open Access

Length of Campus-only Access

None

Document Type

Honors in the Major Thesis

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