Patent application EP19174348A (EP), filed 2019-05-14
Publication number: EP3739503A1
Title: VIDEO PROCESSING
Abstract: [0001]    There is disclosed an apparatus, method and computer program product relating to video processing. The apparatus may comprise means for receiving data representing a first frame of video content comprising a plurality of frames and determining, for at least one object in a first frame, an object type and position in the first frame. The apparatus may also comprise means for determining a number of frames N to skip over based on a comparison of the type and position of the object in the first frame with the type and position of one or more objects in one or more prior frames, and for providing the N+1 frame, and not the skipped-over frames, to means for applying said frame to an image model.
IPC codes: G06K   9/    00            A I
G06V  20/    40            A I
G06V  20/    58            A I
Claims: number: 1
text: An apparatus, comprising means for:
number: 2
text: The apparatus of any preceding claim, wherein determining the object type and position in the first frame comprises identifying a plurality of objects in the first frame, determining for each object the object type and position in the first frame, and wherein determining the number of frames N to skip over is based on a comparison of the respective types and positions of all objects in the first frame with the types and positions of one or more objects in one or more prior frames.
number: 3
text: The apparatus of claim 1 or claim 2, wherein the means is further configured to receive subsequent frame of video content of the plurality of frames and repeat the determining and providing operations for said subsequent frames.
number: 4
text: The apparatus of any preceding claim, wherein the means is configured to determine the number of frames N to skip over using a policy model which receives as input a state parameter S indicative of the respective type and position of the one or more objects in the first, or any subsequent frame.
number: 5
text: The apparatus of claim 4, wherein the policy model is a pre-trained policy model.
number: 6
text: The apparatus of claim 5, wherein the policy model is pre-trained using a reinforced learning method.
number: 7
text: The apparatus of claim 6, wherein the policy model is trained by means of using a reinforced learning method which takes as input a plurality of training images and an object detection model for determining key frames in the plurality of training images, wherein the reinforced learning method uses a reward function that rewards, for given states, an increase in the number of frames N skipped over, whilst penalizing the skipping over of determined key frames.
number: 8
text: The apparatus of claim 7, wherein the object detection model determines key frames as frames in which new objects appear or object transitions occur.
number: 9
text: The apparatus of any preceding claim, wherein the image model processing means is remote from the apparatus.
number: 10
text: The apparatus of any preceding claim, wherein the image model processing means is a computational model for analysing provided frames and for producing inference output.
number: 11
text: The apparatus of any preceding claim, wherein the means comprises:
number: 12
text: A method, comprising:
number: 13
text: A non-transitory computer readable medium comprising program instructions stored thereon for performing a method, comprising:
number: 14
text: Apparatus comprising means for:
number: 15
text: A method, comprising:
Office action: search_report, dated 2020-11-18
Rejection reasons: novelty_epc_54
Prior art cited: ref_id: WO2013146737A1
ref_type: patent
severity: background
ref_id: US7095786B1
ref_type: patent
severity: background
ref_id: CN109409221A
ref_type: patent
severity: background
ref_id: US7095786
ref_type: patent
severity: novelty_destroying
ref_id: CN109409221
ref_type: patent
severity: background
Final disposition: pending (2020-11-18)