FACE DETECTION AND TRACKING METHOD

• US 20090169067A1
• Filed: 12/29/2008
• Published: 07/02/2009
• Est. Priority Date: 12/26/2007
• Status: Abandoned Application

• Current Assignee: Altek Corporation
• Original Assignee: Altek Corporation
• Inventors: CHOU, Hong-Long, YANG, Tai-Chang, CHANG, Yin-Pin
• Application Number:
  US12/344,813
• Publication Number:
  US 20090169067A1
• Time in Patent Office: Days
• US Class Current: 382/118
• CPC Class Codes: G06V 40/173 face re-identification, e.g. recognising unknown faces across different face tracks

Abstract

Face detection and tracking method is executed by a computer or a microprocessor with computing capability for identifying human faces and positions thereof in image frames. First, face detection is performed to detect human faces in a plurality of frames. Then, face tracking is performed on each of the frames to track the detected human faces and record positions of these human faces. Afterward, face detection on the image frames is again performed every few frames, skipping the positions of the human faces that have been recorded, so as to quickly search for other human faces that might be newly added.

Claims

1. A face detection and tracking method, carried out by a computer or a microprocessor with computing capability, the method comprising:

performing a face detection to detect human faces in a plurality of frames;

performing a face tracking on each of the plurality of frames to track the detected human faces and record positions of the human faces; and

performing a face detection again every few frames while skipping the recorded positions of the human faces.

2. The face detection and tracking method as claimed in claim 1, wherein the face detection comprises:

(a) performing an edge detection respectively on the frames to obtain an edge image;

(b) dividing the edge image into structures with blocks of equal sizes according to dimensions of human face features; and

(c) comparing each of the blocks in the edge image to see whether any images matching the human face features exist.

3. The face detection and tracking method as claimed in claim 2, wherein the face detection further comprises:

sequentially dividing the edge image into structures with blocks of equal sizes according to dimensions of a number of human face features of unequal sizes; and

sequentially carrying out the steps (a), (b), and (c) of face detection according to the human face features, so as to find out the images matching the human face features.

4. The face detection and tracking method as claimed in claim 3, further comprising:

simultaneously performing a face detection and a face tracking in a thread, the face detection compares in the frames the images matching the human face features, and the steps (a), (b), and (c) of face detection are performed on a single frame according to only one human face feature.

5. The face detection and tracking method as claimed in claim 1, wherein the face tracking is performed by a method selected from a group consisting of an image differencing method, a moving edge detection method, and a trust-region method.

6. The face detection and tracking method as claimed in claim 5, wherein the image differencing method compares to see a pixel difference between a current frame and a previous one, so as to find out the positions of the human face images after moving.

7. The face detection and tracking method as claimed in claim 5, wherein the moving edge detection method comprises:

obtaining a pixel difference between a current frame and a previous one as a first differential frame, and performing an edge treatment on the first differential frame;

obtaining a pixel difference between the previous two frames as a second differential frame, and performing an edge treatment on the second differential frame; and

multiplying the treated first and second differential frames to obtain the positions of the human faces after moving.

8. The face detection and tracking method as claimed in claim 5, wherein the trust-region method searches in a preset range around corresponding positions in a current frame according to the positions of the human faces in a previous frame to see whether any human face images matching the human face features exist, and records the positions of the human face images.