Method and apparatus for processing pictures of mobile object

• US 7,701,482 B2
• Filed: 08/09/2005
• Issued: 04/20/2010
• Est. Priority Date: 06/21/2001
• Status: Active Grant

• Current Assignee: Socionext Inc., The Foundation for the Promotion of Industrial Science
• Original Assignee: Fujitsu Microelectronics Limited (Fujitsu Limited), The Foundation for the Promotion of Industrial Science
• Inventors: Ikeuchi, Katsushi, Kamijo, Shunsuke, Sakauchi, Masao
• Primary Examiner(s): SENFI, BEHROOZ M
• Application Number:
  US11/199,206
• Publication Number:
  US 20050285939A1
• Time in Patent Office: 1,715 Days
• Field of Search: 348/148, 348/149, 348/135, 348/118, 348/113, 348/119, 348/25, 348/142, 348/160, 348/117, 382/209, 382/30, 382/171, 382/31, 382/104, 382/172, 382/106, 382/372, 382/162, 382/163, 382/164, 382/168, 382/276, 382/282, 701/117, 701/118, 701/301, 701/119, 701/300, 701/121, 701/302, 701/122, 701/120
• US Class Current: 348/149
• CPC Class Codes: G06T 2207/10016 Video; Image sequence
• CPC Class Codes: G06T 2207/30236 Traffic on road, railway or crossing
• CPC Class Codes: G06T 7/20 Analysis of motion motion estimation for coding, decoding, compressing or decompressing digital video signals H04N19/43, H04N19/51
• CPC Class Codes: G06T 7/231 using full search
• CPC Class Codes: G06V 20/40 in video content extracting overlay text G06V20/62; video retrieval G06F16/70; processing of video elementary streams in video servers H04N21/234; processing of video elementary streams in video clients H04N21/44
• CPC Class Codes: G06V 20/54 of traffic, e.g. cars on the road, trains or boats
• CPC Class Codes: G06V 40/20 Movements or behaviour, e.g. gesture recognition recognition of facial expressions G06V40/16
• CPC Class Codes: G08G 1/04 using optical or ultrasonic detectors
• CPC Class Codes: G08G 1/164 Centralised systems, e.g. external to vehicles

Abstract

A feature amount of an inter-mobile unit relative movement are detected as an observation amount by an observation amount detecting section 26, time series of the observation amounts are stored as an observation series into a storage section 27 to calculate a similarity of the observation series to a predetermined collision observation series by a classification section 28. A determination section 29 determines to be a collision accident if, in a case where the similarity is larger than a predetermined value, a mobile unit associated with the similarity is at rest in a stoppage prohibition area set in a storage section 30 and another mobile unit is moving, and to be a mobile unit failure if collision determination conditions except for the similarity are met. By consisting of not only a first scalar obtained by quantizing a relative velocity vector between mobile units but also a second scalar obtained by quantizing a relative position vector between mobile units as the observation amount, a relative movement between mobile units is classified in more detail. A mobile unit is tracked in units of block by a mobile unit tracking section 25 to discriminate overlapped mobile units in pictures.

Claims

1. An inter-mobile unit movement classification method of processing time series pictures to classify a movement between mobile units in at least one of said pictures, comprising:

detecting, with a processor, a feature amount of a relative movement of a second mobile unit with respect to a first mobile unit as an observation amount to store a time series of said observation amounts as an observation series;

calculating, with the processor, a similarity of said observation series to a reference series, said reference series including designated previously recorded observation series of inter-mobile unit movement; and

classifying, with the processor, a movement of said second object with respect to said first mobile unit according to a value of said similarity,

wherein said observation amounts each include;

a first scalar obtained by quantizing an amount associated with both a relative velocity V of said second mobile unit with respect to said first mobile unit and a distance d between said first and second mobile units; and

a second scalar obtained by quantizing a relative position vector of said second mobile unit with respect to said first mobile unit; and

said first scalar is a value obtained by quantizing V·

f(d), where f(d) is a monotone decreasing function of said distance d.

2. The inter-mobile unit movement classification method according to claim 1, wherein said f(d) is expressed as k/(d+ε

), where ε and

k are positive constants.

3. The inter-mobile unit movement classification method according to claim 1, wherein said similarity is a probability that said observation series arises, said probability is a value calculated on the basis of a hidden Markov model, and said reference series is a learning series for determining a model parameter.

4. An inter-mobile unit movement classification apparatus comprising:

a picture storage device storing time series pictures; and

a picture processing device processing said time series pictures to detect an anomaly of a mobile unit in at least one of said pictures,

wherein said picture processing device comprises

an observation amount detecting section detecting a feature amount of a relative movement of a second mobile unit with respect to a first mobile unit as an observation amount;

an observation series storage section storing a time series of said observation amounts as an observation series;

a similarity calculation section calculating a similarity of said observation series to a reference series, said reference series including designated previously recorded observation series of inter-mobile unit movement; and

a classification section classifying a movement of said second object with respect to said first mobile unit according to a value of said similarity;

wherein said observation amounts each include;

a first scalar obtained by quantizing an amount associated with both a relative velocity V of said second mobile unit with respect to said first mobile unit and a distance d between said first and second mobile units; and

a second scalar obtained by quantizing a relative position vector of said second mobile unit with respect to said first mobile unit; and

said first scalar is a value obtained by quantizing V·

f(d), where f(d) is a monotone decreasing function of said distance d.

5. The inter-mobile unit movement classification apparatus according to claim 4, wherein said f(d) is expressed as k/(d+ε

), where ε and

k are positive constants.

6. The inter-mobile unit movement classification apparatus according to claim 4, wherein said similarity is a probability that said observation series arises, said probability is a value calculated on the basis of a hidden Markov model, and said reference series is a learning series for determining a model parameter.

7. A method of processing time series pictures to classify a movement between mobile units, the method comprising:

detecting, with a processor, an amount of relative movement of a second mobile unit with respect to a first mobile unit to store a time series of the detected relative movement;

calculating, with the processor, a similarity of the time series to one or more designated previously recorded reference series of inter-mobile unit movement; and

classifying, with the processor, a movement of said second object with respect to said first mobile unit according to the calculated similarity;

wherein the detected relative movement includes a scalar obtained by quantizing an amount associated with both a relative velocity V of the second mobile unit, with respect to the first mobile unit, and a distance d between the first and second mobile units, the scalar being obtained by quantizing V·

f(d), where f(d) is a monotone decreasing function of said distance d.