The measurement of behavior for participants in a conversation scene involves verbal and nonverbal communications. The measurement validity may vary depending on the observers caused by some aspects such as human error, poorly designed measurement systems, and inadequate observer training. Although some systems have been introduced in previous studies to automatically measure the behaviors, these systems prevent participants to talk in a natural way. In this study, we propose a software application program to automatically analyze behaviors of the participants including utterances, facial expressions (happy or neutral), head nods, and poses using only a single omnidirectional camera. The camera is small enough to be embedded into a table to allow participants to have spontaneous conversation. The proposed software utilizes facial feature tracking based on constrained local model to observe the changes of the facial features captured by the camera, and the Japanese female facial expression database to recognize expressions. Our experiment results show that there are significant correlations between measurements observed by the observers and by the software.